Mind candy mystery novels. The first is a combination of a procedural and
an amateur-sleuth mystery; the second is just a procedural. They're well-told,
with good characterization, but too many coincidences for me to be completely
satisfied in a mystery. (Picked up because of the quality of Wood's
older science fiction and fantasy, particularly
Looking for the Mahdi and Bloodrights.)
The CMU Statistics Department is
conducting two faculty
searches, one for teaching-track and one for tenure-track faculty, and I
find myself on the search committee. (This feels extra bizarre because I could
swear I just came here about two years ago.) I am, obviously, a partial judge,
but I think we're a great place — I literally cannot think of another
statistics department where I would rather be. We are, this year, making a
very serious attempt to reach out to people from backgrounds which might lead
them to not normally think they'd have a chance here. I think I can guarantee
that this year, at least, the idea of a "related area" will
be interpreted quite liberally. We are
also quite serious about wanting to improve our track-record when it comes to
hiring women (nothing to brag about) and under-represented minorities
(really nothing to brag about), and not just for faculty but also for
graduate students. If readers have any questions, I promise to promptly answer
any serious inquiry.
"Inference in the Presence of Network Dependence Due to Contagion" (Next Week at the Statistics Seminar)
Attention conservation notice: Only of interest if you (1) care
about statistical inference with network data, and (2) will be in Pittsburgh next week.
A (perhaps) too-skeptical view of statistics is that we should always think
we have $ n=1 $, because our data set is a single, effectively irreproducible,
object. With a lot of care and trouble, we can obtain things very close to
independent samples in surveys and experiments. When we get to time series or
spatial data, independence becomes a myth we must abandon, but we
still hope that we can break up the data set into many
nearly-independent chunks. To make those ideas plausible, though, we need
to have observations which are widely separated from each other. And those
asymptotic-independence stories themselves seem like myths when we come to
networks,
where, famously, everyone
is close to everyone else. The skeptic would, at this point, refrain from
drawing any inference whatsoever from network data. Fortunately for the
discipline, Betsy Ogburn is not such a skeptic.
Elizabeth Ogburn, "Inference in the Presence of Network Dependence Due to Contagion"
Abstract: Interest in and availability of social network data has led to increasing attempts to make causal and statistical inferences using data collected from subjects linked by social network ties. But inference about all kinds of estimands, starting with simple sample means, is challenging when only a single network of non-independent observations is available. There is a dearth of principled methods for dealing with the dependence that such observations can manifest. We describe methods for causal and semiparametric inference when the dependence is due solely to the transmission of information or outcomes along network ties.
Time and place: 4--5 pm on Monday, 16 November 2015, in 1112 Doherty Hall
As always, the talk is free and open to the public.
"Statistical Estimation with Random Forests" (This Week at the Statistics Seminar)
Attention conservation notice: Only of interest if you (1) are
interested in seeing machine learning methods turned (back) into ordinary inferential statistics, and (2) will be in Pittsburgh on Wednesday.
Leo Breiman's random forests have long been one of the poster children for
what he called
"algorithmic models", detached from his "data models" of data-generating
processes. I am not sure whether developing classical, data-model
statistical-inferential theory for random forests would please him, or has him
spinning in his grave, but either way I'm sure it will make for an interesting
talk.
Stefan Wager, "Statistical Estimation with Random Forests"
Abstract: Random forests, introduced
by Breiman (2001), are
among the most widely used machine learning algorithms today, with applications
in fields as varied as ecology, genetics, and remote sensing. Random forests
have been found empirically to fit complex interactions in high dimensions, all
while remaining strikingly resilient to overfitting. In principle, these
qualities ought to also make random forests good statistical estimators.
However, our current understanding of the statistics of random forest
predictions is not good enough to make random forests usable as a part of a
standard applied statistics pipeline: in particular, we lack robust consistency
guarantees and asymptotic inferential tools. In this talk, I will present some
recent results that seek to overcome these limitations. The first half of the
talk develops a Gaussian theory for random forests in low dimensions that
allows for valid asymptotic inference, and applies the resulting methodology to
the problem of heterogeneous treatment effect estimation. The second half of
the talk then considers high-dimensional properties of regression trees and
forests in a setting motivated by the work
of Berk et al. (2013) on valid
post-selection inference; at a high level, we find that the amount by which a
random forest can overfit to training data scales only logarithmically in the
ambient dimension of the problem.
(This talk is based on joint work with Susan Athey, Brad Efron,
Trevor Hastie, and Guenther Walther.)
Time and place: 4--5 pm on Wednesday, 11 November 2015 in Doherty Hall 1112
As always, the talk is free and open to the public.
Blogging will remain sparse while I teach, finish
the book, write
grant proposals, try not to screw up being involved in a faculty
search, do all the REDACTED BECAUSE PRIVATE things, and dream about
research. In the meanwhile:
A Twitter account, opened
at Tim Danford's instigation. This
is a semi-automated new account which is just for announcing new posts here; it
(and I use the pronoun deliberately) follows no one, I read nothing, and
messages or attempts to engage might as well be piped
to /dev/null.
My online notebooks are in the same process of incremental update they've been for the last 21 years.
Mind candy, sequel
to Summoned
(which I seem not to have blogged about), being the further education of a
Lovecraftian sorcerer. Pillsworth tries very hard to maintain faithfulness to
the canon, but with a sensibility which is a just a bit less freaked
by its own attraction to the not-like-me than Lovecraft was. It's clearly
aimed at younger readers, but I'm not sure how many of them will have read
enough eighty-year-old stories to appreciate it.
Mind candy: the adventurous life of a travel-book editor, who discovers
that the big city is, in fact, full of monsters — and she is, arguably,
one of them.
I remember this being a favorite book as a teenager, but I'd not read it
for decades. It turns out I'd forgotten the last half or so, and it blew me
away, again.
Very old-school, but very clear, experimental design; Kempthorne is
extremely sound on the role of randomization, and what it does and does not let
one estimate. Reading this now, it's amazing just how little one could
actually calculate back then, outside of additive-and-Gaussian models,
and so how much of the formal machinery was really about simplifying
calculations. (Look at the gyrations he goes through to avoid having to
explicitly invert matrices when getting least-squares estimates.)
Mind candy, of a very odd sort; only semi-recommended. On the surface,
it's a dark historical fantasy set in rural 19th century England, complete with
scenes of village life and a haunted mansion. The deeper in one goes, the more
elements appear which are bizarre even for such a book — elements which
are never explained. My best guess — n cnenyyry jbeyq jubfr uhzna vaunovgnagf ner qrfpraq sebz crbcyr
jub pnzr sebz Ivpgbevna Oevgnva naq uryq ba gb gubfr zberf gb n evqvphybhf
rkgrag (qryvorengr geniryref? fangpurq ol fbzr zlfgrevbhf sbepr? zreryl
ivpgvzf bs enaqbz vagreqvzrafvbany jrveqarff?), cyhf n ybg bs ceruvfgbevp
navznyf rkgvapg va bhe jbeyq, oebhtug bire ol gur fnzr cebprff — turns
out to be not
what the author had in mind, though not that far off either. This setting,
I have to say, did nothing for me, but I can see how many would like it
(*), and Barlough certainly has real skills as a novelist.
*:
Bgure crbcyr zvtug fcrphyngr ba gur nccrny
bs na vzntvanel jbeyq jurer gur fbyr yvtug bs pvivyvmngvba vf na Nzrevpna jrfg
pbnfg vf ragveryl vaunovgrq ol JNFCf, jub qvqa'g rira unir
gb rkgrezvangr nal angvirf gb trg gur ynaq, ohg jung qb V xabj
nobhg Oneybhtu'f zbgvirf, be gur sne zber inevbhf barf bs uvf snaf? Jung V pna
fnl pbasvqragyl gung, nf n jbex bs fcrphyngvir svpgvba, gur jbeyq-ohvyqvat vf
ynhtunoyl jrnx.
Gung na nygreangr irefvba bs bhe jbeyq jurer gur Vpr Ntrf
arire raqrq, jurer gurer vf ab thacbjqre, naq jurer gur Nzrevpnf jrer
havaunovgrq orsber Rhebcrnaf cynagrq frggyre pbybavrf, jbhyq unir
n Oevgnva, zhpu yrff bar jubfr phygher va 1839 jnf whfg yvxr jung vg
jnf urer, fubjf n gbgny snvyher bs uvfgbevpny frafr.
Guvf vf bayl zngpurq ol
gur vqrn gung n praghel naq n unys yngre, nsgre n tybony raivebazragny
pngnfgebcur vapyhqvat, nzbat bgure guvatf, gur gbgny qvfehcgvba bs nyy
ybat-qvfgnapr genqr, gung phygher jbhyq erznva pbzcyrgryl hapunatrq. (Naq vg
qbrfa'g rira frrz gb or gung gurl bayl guvax gurl'ir cerfreirq guvatf
hapunatrq.)
Jbeyq-ohvyqvat vf, bs pbhefr, abg gur bayl iveghr sbe fcrphyngvir
svpgvba --- zhpu gur fnzr pevgvpvfzf nccyl, zhgngvf zhgnaqvf, gb Anbzv Abivx'f
vzzrafryl sha Ancbyrbavp frn qentba fgbevrf --- ohg urer
vg xrcg wneevat zr.
I say this as someone who likes the idea of a North America which
still has all the old Pleistocene megafauna.
Mind candy: a collection of his horror stories, though two of these are
really too long to be stories ("The Buffalo Hunter", 130 pages; "Mrs. God",
166). "Blue Rose" and "The Juniper Tree" were fine (they relate to Straub's
novels, but stand alone); I did not care for "The Buffalo Hunter" at all. "A
Short Guide to the City" is creepy (*), as is "Something About a Death,
Something About a Fire"; in neither story does much of anything at all happen.
"Mrs. God", finally, is a Gothic extravagance with a haunted stately house,
hostile villagers, mysterious manuscripts, eerie parallels across generations,
morally and biologically decayed aristocrats, a viewpoint character who doesn't
so much have perceptions as a continuous running pathetic fallacy, and, because
this is Straub, poetry. (Also, again because this is Straub, no explanations
of anything at all.)
*: And, I'm afraid, just a bit racist in the way it describes the South
Siders. Which is a shame, because that bit is also one of the best parts of
the story.
At the end of the last volume, I
thought there was no way this series could be satisfyingly finished in one more
book. I should have had more trust in the author.
Spoiler-ish comments:
V qvqa'g frr ubj Oerd pbhyq cbffvoyl jva
ntnvafg Nannaqre Zvnannv --- abe qvq V guvax gung nsgre nyy guvf, Yrpxvr jnf
tbvat gb unir Oerd hygvzngryl qrsrngrq. (Gubhtu n zrnare nhgube zvtug unir.)
Jung V qvq abg pbhag ba jnf Oerd'f zvffvba bs crefbany ergevohgvba ribyivat
vagb na NV yvorengvba zbirzrag, phyzvangvat va sbhaqvat gur Phygher.
Mind candy fantasy epic. I picked this up on the recommendation
of Kameron Hurley, and was not disappointed: it is the only fantasy
novel I have run across which turns on questions of economics and imperialism,
and still manages to avoid cynicism. (Which, come to think of it, is
hard with realist fiction.) Further comments ROT-13'd for spoilers:
Gung
Oneh jbhyq orgenl gur eroryyvba jnf boivbhf rabhtu gb zr sebz gur zbzrag gur
ercerfragngvir bs gur Uvqqra Znfgref znqr pbagnpg jvgu ure --- uryy, boivbhf
rabhtu sebz gur gvgyr. Rira gur trareny angher bs gur svany grfg jnf boivbhf.
Naq lrg vg fgvyy jnf dhvgr nssrpgvat, qrfcvgr zl univat abguvat crefbanyyl
vairfgrq Oneh'f cnegvphyne inevrgl bs sbeovqqra ybir.
Whether Baru emerges at the end triumphant yet tragic, or merely tragic, I
hesitate to say.
This divides fairly cleanly into three parts. The first is about the history of
Sher Shah Sur, who,
depending on your perspective, either was the successor to the Afghan
(=Pashtun, pretty
much) Lodi dynasty as
sultan of Delhi and emperor of Hindustan, or was a rebel against the
Timurids, temporarily
expelling Humayun and
setting the stage for Akbar.
Aquil does a good job of setting out all the accouns from all the primary
sources, which left me, at least, in a great deal of doubt about what exactly
happened when. The second part is about the administration of the Afghan
dynasties and their incorporation of local Rajputs into their imperial project.
The third is about the political role of Sufi orders (including their stories
about beating Hindu yogis in displays of supernatural force; disappointingly,
Aquil does not inquire what stories contemporary yogis told about sufis) and
the role of sufis in cross-religious syncretism. These are only loosely
coupled to each other, though there are some connections.
Aquil presumes a reader familiar with at least the outlines of the
political and religious history of northern India during the 15th and 16th
centuries, and makes no concession to ignorance on this score. (I am not
ashamed to admit how much I relied on my memories
of Amar Chitra Katha
comics read as boy.) With even the minimal necessary background, however, he
has some fascinating things to say, both about massive empires rising and
falling over little more than a decade, and how this was intertwined with both
profound mystical spirituality and gross superstition (with, naturally, the
superstition predominating).
Sequel to First Light,
where the consequences of that adventure come home to roost. — If I say
that these novels are near-future military hard science fiction, full of
descriptions of imaginary technologies and of stuff blowing up, and clearly
inspired by an anxious vision of America's ongoing decline, I am being
perfectly truthful, and yet also quite misleading. People who enjoy books
which fall under that rubric will find it very much the sort of thing they
like; at the same time, normally I'd pay to avoid having to read such works,
and yet found these two quite compelling, and eagerly await the conclusion.
Hard-SF space opera, set in the same future as his terrific
The Quiet War and Gardens of the Sun, but many
centuries later. (He's good at filling in enough of the back-story to make it
separately readable.) In this book, we're plunged into a conflict over the
star system around Fomalhaut among four different
more-or-less-post-more-or-less-human clades, seen from three points of view,
two of which prove to be peripheral grunts. (Spoiler: Jung, rneyl ba, nccrnef gb or bar bs gur zbfg uhzna ivrjcbvagf
cebirf, va snpg, gb or cebsbhaqyl fgenatr, gubhtu guvf vf fbzrguvat ernqref bs
gur cerivbhf obbx pbhyq thrff.) I thought it was very good, though not quite
as great as those two earlier books.
A decent collection of essays, and really pretty photos, on the natural and
human history of what is today a bike route
from Pittsburgh to Cumberland, Maryland (and
so on
to Washignton, D.C.), but has had a lot of other incarnations over the
centuries. Of only local interest, but locally interesting.
Mind candy mystery: In which
the Satanic
panic of the 1980s meets the economic collapse of family farming, and makes
for something bitterly poisonous and engrossing. (Though arguably not as
poisonous as some of
what actually
happened back then.)
Photos, collages and a translated story, meant to illustrate the
contemporary life of the Uighurs in Xinjiang.
Bought from the
author; I learned about it from
the New
York Review blog.
I picked up this middle volume of a trilogy, without having read the first
book, because someone left it in a free-books pile at work, and I was curious.
Whoever got rid of their copy: thanks. This is a truly fascinating look at the
development of the market economy and capitalism
in early modern
Europe, and to some extent in the rest of the old world at the same time,
full of fascinating information (*) and perspectives, as well as chewy and
questionable hypotheses.
One notable feature, for me, is that Braudel wants to distinguish between
the development of a market economy and the development of capitalism. He does
this not to suggest an early-modern pre-history
for market
socialism, but because he identifies capitalism with "the realm of
investment and of a high rate of capital formation", i.e., the activities of
men, and of firms, who made substantial investments of money which resulted, or
could result, in high rates of return. This was, in this period, in finance
(especially financing the developing sovereign territorial states), in
long-distance trade, and in monopolies. These were activities which could
hardly have gotten off the ground without a large market economy around them,
but where competition was precisely what one would want to avoid...
I wish someone had told me before this that Braudel was a good writer, and
not just an important historian. Also: I'd have given a lot to see what he
might have made of
the "new
international trade theory" and "new economic geography", which were just
forming at the time he was writing.
*: The bit on p. 556 where he says that a
"prohibition on lending at interest" was a "condition not present in Islam" was
rather boggling, and does
leave me wondering about the accuracy of some of his other
statements.
The story of the American conquest of Hawaii, told in Vowell's signature
style. (It works better read aloud than on the silent page.) With many thanks
to "Uncle Jan" for my copy.
Mind candy: space opera, in which the Culture, in its own inimitable
fashion, harrows Hell. Somewhat longer, I think, than it needed to be, but
still compulsively readable.
Mind candy, at the urban fantasy / horror border, in which Vancouver's art
scene confronts an outbreak from the dungeon dimensions — or, more
exactly, Carcosa. I quite enjoyed how Downum is able to use pretty much the
full canonical Cthulhu Mythos, from the seventy steps down to the Dreamlands to
night-gaunts and everything else, and manage to make it seem not a formulaic
exercise but genuinely creepy. (And I mean "creepy" in the "hairs standing on
the back of the neck" sense, not the "bigoted distant connection at
Thanksgiving" [*] sense, which says something considering the source material.)
I have the impression this novel didn't make much of an impact when it came
out, but if so that's unfair.
*: Of course I'm not thinking of you, dear
distant connection with whom I have shared Thanksgiving.
Mind-candy contemporary fantasy in which discovering that her biological
parents are convicted serial killers is the least of the protagonist's
problems. (Previously.)
This is a very nicely done popular history of not just the
teaching profession but also of the public schools, and just why both have been
such a point of political contention for so long — and why we keep trying
incredibly similar fixes time after time. Because it's not an academic tome,
it doesn't attempt to be altogether comprehensive, rather a series of portraits
of particular episodes, but so far as an interested non-expert can judge, those
episodes are well-chosen and the background to the portraits accurate.
"Robust Confidence Intervals via Kendall's Tau for Transelliptical Graphical Models" (Next Week at the Statistics Seminar)
Attention conservation notice: Publicity for an upcoming
academic talk, of interest only if (1) you care about quantifying uncertainty
in statistics, and (2) will be in Pittsburgh on Monday.
I am late in publicizing this, but hope it will help drum up attendance
anyway:
Mladen Kolar, "Robust Confidence Intervals via Kendall's Tau for Transelliptical Graphical Models"
Abstract: Undirected graphical models are used extensively in the
biological and social sciences to encode a pattern of conditional independences
between variables, where the absence of an edge between two nodes $a$ and $b$
indicates that the corresponding two variables $X_a$ and $X_b$ are believed to
be conditionally independent, after controlling for all other measured
variables. In the Gaussian case, conditional independence corresponds to a
zero entry in the precision matrix $\Omega$ (the inverse of the covariance
matrix $\Sigma$). Real data often exhibits heavy tail dependence between
variables, which cannot be captured by the commonly-used Gaussian or
nonparanormal (Gaussian copula) graphical models. In this paper, we study the
transelliptical model, an elliptical copula model that generalizes Gaussian and
nonparanormal models to a broader family of distributions. We propose the
ROCKET method, which constructs an estimator of $\Omega_{ab}$ that we prove to
be asymptotically normal under mild assumptions. Empirically, ROCKET
outperforms the nonparanormal and Gaussian models in terms of achieving
accurate inference on simulated data. We also compare the three methods on
real data (daily stock returns), and find that the ROCKET estimator is the only
method whose behavior across subsamples agrees with the distribution predicted
by the theory. (Joint work with Rina Foygel Barber.)
Time and place: 4--5 pm on Monday, 28 September 2015, in Doherty Hall 1112.
As always, the talk is free and open to the public.
On the Nature of Things Humanity Was Not Meant to Know
Attention
conservation notice: A ponderous, scholastic joke, which could only
hope to be amusing to those who combine a geeky enthusiasm for over-written
horror stories from the early 20th century with nerdy enthusiasm for truly
ancient books.
I wish to draw attention to certain parallels between De Rerum
Natura, an ancient epic and didactic poem expounding a philosophy which
is blasphemous according to nearly* every religion, and
the Necronomicon, a fictitious book of magic supposedly expounding
a doctrine which is blasphemous according to nearly** every religion.
The Necronomicon was, of course,
invented
by H. P. Lovecraft for his stories in the 1920s and 1930s. In his mythos,
it was written by the mad poet "Abdul Alhazred", who died in +738 by being torn
apart by invisible monsters. The book then led a twisty life through a thin
succession of manuscript copies and translations, rare and almost lost. The
book was, supposedly, full of the horrible, nearly indescribable, secrets of
the universe: explaining how the world is an uncaring yet quite material place,
in which the
Earth's past
and future are full of monsters, but natural monsters, how the reign of
humanity is a transient episode, and the gods are in reality powerful
extra-terrestrial beings, without any particular care for humanity. Reading
the Necronomicon drives one mad, or at the very least the
frightful knowledge it imparts permanently warps the mind. There are,
supposedly, about half-a-dozen copies in existence, kept under lock and key
(except
when the
story requires otherwise).
De Rerum Natura ("On the Nature of Things") is an
entirely real book,
written by the poet Titus Lucretius Carus around
-55; according to
legend, the poet went mad and died as a result of taking a love potion.
The book thereafter led a twisty life through a thin trail of manuscript
copies, and was almost lost over the course of the middle ages. The book is
quite definitely full of what Lucretius thought of as the secrets of the
universe (whose resistance to description is a runningtheme): how the entire
universe is material and everything arises from the fortuitous concourse of
atoms, how every phenomenon not matter how puzzling has a rational and material
explanation, how
there is
no after-life to fear. It describes how the
Earth's
past was full of thoroughly-natural monsters,
the reign
of humanity and even the existence of the Earth is a transient episode, and
how the gods are in
reality powerful
extra-terrestrial beings without any particular care for humanity, living
(a Lovecraftian touch) in the spaces
between worlds. In the centuries since its recovery, it has been
retrospectively elevated into one of the great books of the Western
civilization (whatever that is).
And thus you will gain knowledge, guided by a little labor,
For one thing will illuminate the next, and blinding night
Won't steal your way; all secrets will be opened to your sight,
One truth illuminate another, as light kindles light.
*: I insert the qualifier for the sake of my Unitarian Universalist friends. ^
**: I insert the qualifier for the sake of my Unitarian Universalist friends. ^
Spoiling the conceit: I
have no reason to believe that Lovecraft was thinking of Lucretius at any point
in writing any of his stories featuring the Necronomicon, or even
that the history of De Rerum Natura influenced the "forbidden
tome" motif
which Lovecraft drew on (and amplified). I also do not think that the
Enlightenment is really about "shouting and killing and revelling in joy".
(Though it would be its own kind of betrayal of the Enlightenment for one of
its admirers, like me, not to face up to the ways some of its ideas have been
used to justify very great evils, particularly when Europeans imposed
themselves on less powerful peoples elsewhere.) Rather, this is all the result
of the collision in my head of
Ada
Palmer's interview by Henry Farrell with Palmer's
earlier appreciation of Ruthanna
Emrys's "Litany of Earth",
plus Ken
MacLeod's cometary Lucretian deities, and early imprinting
on Bruce
Sterling.
Finally, I would pay good money to read the alternate history where it was
the Necronomicon which humanists discovered mouldering in a
monastic library and revived, where its ideas are as thoroughly normalized,
pervasive and surpassed as Lucretius's are, and copies of Kitab
al-Azif can
be found in
any bookstore as a Penguin Classic, translated by
a distinguished contemporary
poet. Failing that, I would like to read Lucretius's explanation of why we
need have no fear of shoggoths.
"Reproducibility and Reliability in Statistical and Data Driven Research" (Week after Next Coming Soon at the Statistics Seminar)
Attention conservation notice: Publicity for an upcoming
academic talk, of interest only if (1) you will be in Pittsburgh and (2)
you care about whether scientific research can be reproduced.
The timeliness
of the opening talk of this year's statistics seminar is, in fact, an
un-reproducible, if welcome, coincidence:
Victoria Stodden, "Reproducibility and Reliability in Statistical and Data Driven Research"
Abstract:
The reproducibility and computational inferences from data is widely
recognized as an emerging issue in the scientific reliability of
results. This talk will motivate the rationale for this shift, and
outline the problem of reproducibility. I will then present
ongoing research on several solutions: empirical research on data
and code publication; the pilot project
for large scale validation of statistical findings; and the
"Reproducible Research Standard" for ensuring the distribution of
legally re-usable data and code. If time permits, I will present
early results assessing the reproducibility of published computational
findings. Some of this research is described in my co-edited books,
Implementing Reproducible Research
and Privacy, Big Data, and the Public Good.
Time and place:4--5 pm on Monday, 14 September 2015, in Doherty Hall 1112 see below
As always, the talk is free and open to the public.
Update, 14 September: Prof. Stodden's talk has had to be rescheduled; I will post an update with the new date once I know it.
The Michauds' gorgeous photos from the 1960s and 1970s — mostly of
Afghanistan, but also Turkey, Iran, and India — aptly paired with
Persianate miniature paintings. This is a wonderful book I have coveted for
many years, and I am very pleased to have finally scored a copy I could afford.
Survey of the state of the field as of 2008. It is decent and generally
clear, if not especially fast-paced, and covers ideas about network structure,
percolation, synchronization of oscillators, epidemic models, diffusion of
innovations (mapped on to epidemic models), and Kauffman's Nk model in some
detail. (They're pretty good on linkages between these.) On other biological
processes they are vaguer.
I found the emphasis on results presuming exact power-law degree
distributions less than compelling, and the apologia for this emphasis in the
conclusion surprisingly wrong-headed. (It does no good to defend them as
approximations unless you also show that conclusions continue to hold when the
assumptions are in fact only approximately true --- that there is, as Herbert
Simon once
put it, continuity of approximation. And in many cases, you'd need very
robust continuity of approximation indeed.) But I recognize that I
am abnormally picky about this subject.
ObDisclaimer: I've met Prof. Vespignani once or twice, but I don't think I've ever met or corresponded with the other authors.
Mind candy: First two-thirds of a fantasy trilogy about the adventures of a
pair of teenage shamans. It's surprisingly enjoyable, with surprisingly
effective monsters. The human setting is inspired not by a vaguely feudal
Europe, but by more-or-less Heian-era Japan, though there seems to be no
equivalent of Buddhism (maybe the bit with the monks in the second book?), and
making the !Ainu blonds and redheads hints at pandering to the audience.
This is all about on-line learning and stochastic gradient descent before it was cool:
This monograph addresses the problem of "real-time" curve fitting in the presence of noise, from the computational and statistical viewpoints. Specifically, we examine the problem of nonlinear regression where observations $ \{Y_n: n= 1, 2, \ldots \} $ are made on a time series whose mean-value function $ \{ F_n(\theta) \} $ is known except for a finite number of parameters $ (\theta_1, \theta_2, \ldots \theta_p) = \theta^\prime $. We want to estimate this parameter. In contrast to the traditional formulation, we imagine the data arriving in temporal succession. We require that the estimation be carried out in real time so that, at each instant, the parameter estimate fully reflects all of the currently available data.
The conventional methods of least-squares and maximum-likelihood
estimation ... are inapplicable [because] ... the systems of normal equations that must be solved ... are generally so complex that it is impractical to try to solve them again and again as each new datum arrives.... Consequently, we are
led to consider estimators of the "differential correction" type... defined
recursively. The $ (n+1) $st estimate (based on the first $ n $ observations) is
defined in terms of the $ n $th by an equation of the form
\[
t_{n+1} = t_n + a_n[Y_n - F_n(t_n)]
\]
where $ a_n $ is a suitably chosen sequence of "smoothing" vectors.
(It's not all time series though: section 7.8 sketches applying the idea to
experiments and estimating response surfaces.) Accordingly, most of the book
is about coming up with ways of designing the $ a_n $ to ensure consistency,
i.e., $ t_n \rightarrow \theta $ (in some sense), especially $ a_n $ sequences
which are themselves very fast to compute.
Mathematically, of course, we've got much more powerful machinery for
proving theorems
about stochastic
approximation these days, but Albert and Gardner's methods seem
particularly clear to me. Also, it's more fun to think of these tools being
used to estimate the orbital elements of satellites (as in the
lovingly-detailed section 8.5) than for ad targeting, a.k.a.
commercialized
surveillance.
Lots of overlap with Gaetan
and Guyon's Spatial Statistics and Modeling (unsurprisingly),
though omitting point processes and going at greater depth into the math of
random fields (e.g., spectral representations) on, mostly, regular lattices. I
suspect most readers would be better served by the later book, but this is
a useful reference for me.
An old favorite, re-read after a long interval. It holds up. So:
if you'd like to read a secondary-world fantasy novel where a magic kingdom
gets visited by a horrific and entirely deserved version of the French
Revolution, with well-drawn characters on all sides, written by an author who
clearly learned great lessons from Jack Vance but has very much her own voice,
track this down.
A readable textbook on evolutionary game theory. It's pretty much entirely
devoted to mathematical methods for finding equilibria and deducing long-run
dynamics, as opposed to substantive results about particular games (or even
classes of games). The mathematical background is explained extensively, and
well, in a series of chapter appendices, amounting to maybe a quarter of the
text.
By "population game", Sandholm means one in which large numbers of agents
all play simultaneously, and all agents making the same move receive the same
payoff, which is solely a function of the current distribution of moves over
players. Agents then update their strategies in some way which depends on what
they did, on the pay-off, and perhaps on how many others played various
different moves and their pay-offs. These "revision protocols" give
rise to different evolutionary dynamics, but all ones which are Markov
processes. Over limited stretches of time, these approximate the ordinary
differential equations one gets from looking at the expected rates of change in
strategy frequencies, with the approximation getting closer and closer as the
population grows. Understanding the limiting behavior over indefinitely long
stretches of time is trickier, since various limits (e.g., large population
vs. low noise) do not necessarily yield the same predictions.
For the most part, Sandholm limits himself to revision protocols which have
various reasonable properties, like continuity in the population distribution,
or not requiring too much information of the agents. (The book pays no
attention to empirical evidence about how human beings or other animals act in
strategic or repeated-choice situations.) But he also has (what seems to me to
be) a mildly perverse interest in revision protocols which will converge on
Nash equilibria, not because they are plausible but, as nearly as I can tell,
because this lets evolutionary and classical game theorists live in peace in
the same economics department.
If this isn't already the economists' standard textbook on evolutionary
game theory, it ought to be.
ETA: I really hope this is a different William H. Sandholm.
The end of the Book of the New Sun (previously: 1, 2,
3). I find that I had
retained the bare outlines of the story from when I read it as a boy, but I
must have appreciated almost nothing more than the story, and the sense of a
very strange and very old, worn-out world. (For instance, the concrete
symbols, the parallels, and the parodic inversions of Wolfe's Catholicism must
have gone right over my head...) Having finished it, I continue to wonder at
the sense of unexplained-but-explicable mysteries that Wolfe created (*), and
to be unsure whether it would be possible to solve them by careful study of the
books, or whether only Wolfe knows what he had in mind, or whether he merely
aimed for that very effect and had no definite answers. (The first option
seems too Protestant, too sola scriptura, somehow.)
*: For instance, is "Behind our efforts, let there
be found our efforts" supposed to echo with the way the last chapter says that
behind this Severian, there is another Severian?
Mind candy. I am surprised how sad I am to see this series end. Once
again, Willig does a good job of taking characters who had been merely stock
figures in previous books and turning them into people, while preserving
continuity with those earlier books.
Mind candy: This is nicely creepy, but it goes rather off the rails in the
last part, where Lotz tries to go from localized weirdness to whole countries (and, by implication, the world) heading to hell in hand baskets.
(Chfuvat
gur HF vagb gurbpenpl naq Wncna vagb erivivat gur Terngre Rnfg Nfvna
Pb-Cebfcrevgl Fcurer vf n ybg gb nfx bs guerr jrveq xvqf.) I do like, however,
that she never actually explains what happened.
Zl thrff, onfrq ba gur irel ynfg yvarf, vf gung gur Guerr ner va n
ebyr-cynlvat tnzr, jvgu rirelbar ryfr orvat na ACP, creuncf va n fvzhyngvba.
Minor Bujold, but still Bujold, which is to say this novella leaves me
wanting to read more adorable adventures of Pensic and Desdemona. (For
instance, jung jvyy Cra'f ernpgvba or jura ur naq Qrf ner va n
ebznapr-abiry cybg?)
Mind candy: conclusion to Abercrombie's Viking-ish trilogy
(previously), and just as
compulsively readable. There are some "Nooo!" moments (particularly for
readers of previous books), and lots of bloodshed, brutality and betrayal (as I
said: Viking-ish), but he pulled off an ending which does not show
every hope as false or futile, which is triumph enough for his worlds.
ROT-13'd for spoilers: 1. Guvf obbx nyfb pbasvezf fbzrguvat V'q
fhfcrpgrq fvapr gur ynfg bar, anzryl gung gur jbeyq bs gur Funggrerq Frn vf gur
erzbgr nsgrezngu bs na heona, grpuabybtvpny pvivyvmngvba oybjvat vgfrys hc
— vaqrrq vg frrzf irel yvxryl gung jr ner gur ryirf. 2. V nqzvg V
thrffrq jebat nobhg gur vqragvgl bs gur genvgbe; V'z fgvyy abg fher gung vg
ernyyl svgf jvgu jung'f orra rfgnoyvfurq bs Sngure Lneiv'f punenpgre naq qrrc
phaavat.
Mind candy: seeing something nasty in a central Florida graveyard.
Promising material, but somehow it never came together for me; it may work
better for others.
Dense but very rich; it presumes no prior acquaintance with graph theory or
spatial stochastic processes, but a very good grasp on measure-theoretic
probability, and a lot of mathematical maturity. The first few chapters build
up gradually from an opener on electrical circuits (!) to random spanning
trees, self-avoiding random walks, "influence" theorems and phase transitions,
percolation theory, and random
cluster models. (I must at this point confess that I'd never got
the point of random cluster models before.) Thereafter things become
a bit more miscellaneous, touring the Ising model, the "contact" model of
stochastic epidemics,
other interacting
particle systems, random graphs, and, finally, the Lorentz gas. The
perspective is very much that of a pure probabilist, though mention is made of
applications to, or non-rigorous results from, physics and statistics.
The subtitle promises a lot more than Jardine delivers, which is instead a
series of more-or-less interesting but only slightly connected anecedotes about
Anglo-Dutch high politics and cultural interchange in the 17th century. Since
the century ended with the Netherlands conquering Britain, but somehow not
turning it into a permanent dependency, I'd really like to read a much more
systematic and analytical account.
Very fluffy mind candy: heists
in fantasyland.
I'm not sure they'd have worked in any reading environment other than
trans-continental airplane flights, but they did.
I had resisted reading the last of the Aubrey-Maturin novels until now.
Having done so, I'm not at all sure how I feel about it, because it is so
obviously the opening to a new cycle of novels, which were never written.
Update, next day: added a link to Simon's comment on "continuity
of approximation", and deleted an excessive "very". 4 September:
replaced Simon link with one which should work outside CMU, fixed an
embarrassing typo.
Course Announcement: 36-401, Modern Regression, Fall 2015
For the first time, I will be teaching a section of the course which is the
pre-requisite for my spring advanced data analysis
class. This is an introduction to linear regression modeling for our
third-year undergrads, and others from related majors; my section is currently
eighty students. Course materials, if you have some perverse desire to read
them, will be posted on
the class homepage
twice a week.
This course is the first one in our undergraduate sequence where the
students have to bring together probability, statistical theory, and analysis
of actual data. I have mixed feelings about doing this through linear models.
On the one hand, my experience of applied problems is that there are really
very few situations where the "usual" linear model assumptions can be
maintained in good conscience. On the other hand, I suspect it is
usually easier to teach people the more general ideas if they've thoroughly
learned a concrete special case first; and, perhaps more importantly, whatever
the merits of
(e.g.) Box-Cox
transformations might actually be, it's the sort of thing people will
expect statistics majors to know...
Addendum, later that night: I should have made it clear in the
first place that my syllabus is, up through the second exam, ripped
off borrowed with gratitude
from Rebecca Nugent, who
has taught
401 outstandingly for many years.
Update, since people have asked for it, links here (see the course page for the source files for lectures):
Via I forget who, Darius Kazemi explaining "How I Won the Lottery". The
whole thing absolutely must be watched from beginning to end.
Kazemi is, of course, absolutely correct in every particular. What he says
in his talk about art goes also for science and scholarship. Effort, ability,
networking — these can, maybe, get you more tickets. But success is,
ultimately, chance.
I say this not just because it resonates with
my personal experience, but because of actual
experimental evidence. In a series
of very ingenious
experiments, Matthew Salganik, Peter Dodds and Duncan Watts have
constructed "artificial cultural markets" — music download sites where
they could manipulate how (if at all) previous consumers' choices fed into the
choices of those who came later. In one setting, for example, people saw songs
listed in order of decreasing popularity, but when you came to the website you
were randomly assigned to one of a number of sub-populations, and you only saw
popularity within your sub-population. Simplifying somewhat (read the
papers!), what Salganik et al. showed is that while there is some correlation
in popularity across the different experimental sub-populations, it is quite
weak. Moreover, as in the real world, the distribution of popularity is
ridiculously heavy tailed (and skewed to the right): the same song can end up
dominating the charts or just scraping by, depending entirely on accidents of
chance (or experimental design).
In other words: lottery tickets.
If one has been successful, it is very tempting to think that one
deserves it, that this is somehow reward for merit, that one is
somehow better than those who did not succeed and were not rewarded.
The moral to take from Kazemi, and from Salganik et al., is that while those
who have won the lottery are more likely to have done something to get multiple
tickets than those who haven't, they are intrinsically no better than many
losers. How, then, those who find themselves holding winning tickets should
act is another matter, but at the least they oughtn't to delude themselves
about the source of their good fortune.
This is by now a contemporary classic, which I should have read years ago.
To enjoy it, you need to like geeking out over designing steel boxes; the
culture of longshore work, the politics of their unions, and their (totally
correct) fears of technological obsolescence; why container ports have
economies of scale; and a dozen other things that usually lurk in the
background of our world. If you read this weblog, it's probably right up your
alley.
This is one of the few genuinely-evolutionary ventures in social science
I've ever run across. Spruyt's aim, as his title suggests, is to explain how
Europe came to be dominated into sovereign territorial states, which
subsequently imposed that some mode of organization on the rest of the world.
He wants a genuinely selectionist explanation, which he realizes means he needs
to explain why such states survived, or tended to survive, while other,
contemporary forms of polity did not. And he realizes that there were
alternative forms of polity: not just feudalism, but also city-states (as in
Italy) and city-leagues (as in the north), which were, for a time, serious
contenders. Spruyt is very sound on how the causes which led to the formation
of any of these polities need not be, and generally aren't, the same as the
causes of their ultimate selection. It's very nice to see such a mass of
historical detail intelligently organized and brought to bear on an interesting
theoretical problem.
Being me, naturally I have some qualms or quibbles. (1) Spruyt essentially
looks at three case studies: the French kingdom, the Hanseatic League, and the
city-states of northern Italy. But his account, if valid, should generalize to
at least the rest of Europe; I'd really like to see whether it does. (2) As a
methodological point, the number of polities involved is very small, even if we
go down to treating every city in the low countries or Tuscany as a distinct
unit of selection. On general grounds of evolutionary theory, then, we should
expect noise effects to be quite large relative to fitness differences, which
in turn will make it hard to learn those differences. In other words, with so
few kingdoms, city leagues, etc., to examine, I worry that Spruyt may just be
creating narratives to retrospectively match mere
chance. (The thought experiment here would be something like: in the
alternate history which followed the same path as ours up to, say, 1450, but
thereafter city leagues came to dominate western Europe, how hard would it be
for alternate-Spruyt to assemble the split evidence into a case for the
selective superiority of leagues, over sovereign territorial states?) (3) A
lot of Spruyt's argument for why territorial states did better than city
leagues is that the later lacked a central locus of authority which could
credibly negotiate with outsiders, and make agreements stick by imposing them
on the constituent cities. So why did no one invent the idea of a league where
the league itself was the sovereign? Or was it just that when they did, they
called it the United Provinces, and they happened to form a contiguous
territory? (4) Spruyt takes the rather odd position that variation and
selection are two temporally successive phases of an evolutionary process,
rather than just being logically and causally distinct. (This idea seems to
arise from a rather forced-sounding interpretation of Stephen Jay Gould's
papers on punctuated equilibrium.) This is, I think, both wrong as a matter of
general evolutionary theory, and superfluous to his own actual argument. (5)
The opening chapters spill much too much ink on very parochial internal debates
of the international relations sub-sub-discipline, giving little sense of its
wider relevance to social science.
(Thanks to Henry Farrell for pointing me at this.)
Hurley's earlier science fiction novels
(1, 2)
were enjoyable mind candy, but this is great mind candy:
world-building in which the human, the fantastic, and the all-too-human mingle;
multiple realms of fantastic weirdness; compelling characters; and truly epic
scope to the action. It deserves much more intelligent appreciation, but I am
still too caught up in the story to provide one. I am very impatient
to read the sequels.
The one thing I will raise as a criticism
is that I am pretty sure in twenty years the gender politics here will look as
dated as those in, say, The Forever
War do now. On the other hand, I will not be surprised if people
are still reading this in twenty years; and on the prehensile tail, I
understand why Hurley hit those notes so hard.
Latest installment in the series beginning
with The Atrocity
Archives, in which British secret agents try to deal with the
Cthulhu Mythos and modern management. I doubt it's really that follow-able if
you've not kept up with the series (though I think Stross intends it as an
alternate entry point), so I will cheerfully spoil earlier books in the rest of
this comment. Previous volumes,
through The Rhesus Chart,
have been narrated by IT-staffer Bob; this one by his wife and fellow spook Mo.
As we know from The Jennifer
Morgue, archetypically, Bob is a Bond girl; Mo is Bond. In this
book, Mo is Bond going through a marital collapse, a mid-life crisis,
and a nervous breakdown a bit of a rough patch, so her superiors
respond by putting her in charge of a new department managing superheroes (=
otherwise-innocent bystanders developing sanity- and/or brain- eating magical
powers as the Stars Become Right). Hijinks ensue, for rather soul-destroying
values of hijinks; also, she fights crime.
Mo, as narrator, sounds a bit too much like Bob (for instance, too
many IT allusions, and none arising from music or from epistemology). But
otherwise, it's only too convincing as portrait of a marriage collapsing; I
have more quibbles with the plot. ( Univat rirelguvat or n snyfr-synt bcrengvba ol gur cbyvpr fdhnerf
bqqyl jvgu gur gvzvat bs gur svefg vapvqrag naq vgf crecrgengbe'f qrngu; naq Zb
zhfg'ir orra uvg jvgu n ovt vqvbg fgvpx gb znxr ab pbaarpgvba orgjrra ure
vafgehzrag naq gur ivyynvaf fgrnyvat rfbgrevp zhfvpny fpberf.) On balance,
while I read it in as close to one sitting as I could, I still feel it's below
the peak of the series.
An attempt to argue, as the sub-title says, that the Declaration is at
least as much about equality as it is about freedom, and indeed about equality
as the grounds of freedom. I like it very much, and it is very persuasive; it
makes me feel better about our country. But the big point of doubt I have is
that lots of what Allen points to seems to really be about
a republican form of government, or even what
Bagehot called "government by discussion", which is perfectly
compatible with vast degrees of in-equality.
Disclaimer: I know Prof. Allen, and have participated in a series
of workshops she organized and contributed to
a book she
edited, but I feel under no obligation to write a positive notice of
her books.
I began this one twenty years ago in graduate school, and cannot for the
life of me recall why I didn't finish it at once. (I was young, foolish,
easily misled...) It's best described in the words it uses for one of its own
examples: "a pedagogically ideal illustration of the qualities which made the
graphical method famous: its power to do perturbation theory to infinite order
(thus enabling it to cope with strong couplings beyond the reach of ordinary
perturbation procedures), its highly systematic and so-called 'automatic'
character, its vivid pictorial appeal, and its remarkable talent for producing
results valid outside their region of convergence" (p. 276). It does presume
good knowledge of quantum mechanics and statistical mechanics, but no quantum
field theory is necessary, nor even, I think, precise recall of classical
E&M.
— There must be a general account of when, and why, Feynman diagrams
work for arbitrary Markov processes, and/or other situations where a
probability density obeys a nice differential equation. Where is it? (This is a start.)
Mind candy historical adventure fiction: a tale of derring-do and angst in
the nascent American navy during the war of 1812. It was written before
Williams turned to science fiction, but in retrospect the seeds of a lot of his
later concerns can be discerned here. In particular, the way the viewpoint
protagonist is at once deeply embedded in an institution, indeed commits his
life to it, and also an emotionally detached observer of that institution, will
recur in many later books — I think Favian would have interesting
conversations with Dagmar, Aiah
or Martinez.
(This is the only historical novel I know of which is set during the
Napoleonic Wars, written by an American, and yet does not side with
the British Empire. This partiality towards, if not wholehearted embrace of,
the very system of global conquest, plunder and tyranny against which we fought
the Revolution — the one
which burnt
Washington! — is astonishing. While I am reluctant to question the
patriotism of our historical novelists, is any other conclusion available to
the candid mind?)
Mind candy: literary, historical competence porn*. Praise on my part is
superfluous. Thanks to CM and TC for persuading me to start reading it, and
for providing the term "competence porn".
*: "His speech is low and rapid, his manner
assured; he is at home in courtroom or waterfront, bishop's palace or inn yard.
He can draft a contract, train a falcon, draw a map, stop a street fight,
furnish a house and fix a jury. He will quote you a nice point in the old
authors, from Plato to Plautus and back again. He knows new poetry, and can
say it in Italian. He works all hours, first up and last to bed. He makes
money and he spends it. He will take a bet on anything."
I can't remember having read a better, more comprehensive, clearer, volume
on the theory of nonparametric regression. It is magnificently unconcerned
with the practicalities of applied statistics, but rather relentlessly focused
on determining what we can learn about conditional expectation functions, and
how fast, when we assume basically nothing about those functions, other than
that they are well-defined and we get IID data. (In the last chapters, it even
allows for dependent data.) The coverage is largely organized around different
sorts of models (kernel smoothing, histograms, regression trees, local
polynomials, splines, orthogonal series expansions...), typically beginning by
defining the model, considering the model class's expressive or approximative
powers, and then looking at how quickly it will converge on the true regression
function under various smoothness assumptions on the latter. Classical minimax
theory is used to establish that smoother functions (e.g., those with many
continuous derivative of low magnitude) can be learned more quickly
than rougher functions, but naively, we'd seem to need to know how smooth the
true function is in order to achieve these fast rates. Particularly nice
models are "adaptive", they will automatically adjust to the data and learn
almost as quickly as if they knew in advance how smooth the target was.
Accordingly, a lot of space is given to looking at which methods are adaptive;
many otherwise nice models don't adapt very well. Chapters on topics like
minimax theory and empirical
process theory break up the development of the models, introducing
mathematical tools and general ideas as needed. Two chapters on
cross-validation and data-splitting are particularly nice: everyone uses them,
because they work, but there is surprisingly little theory about such important
tools, and the results here are really quite illuminating.
In principle, all this book requires is a good grasp of probability theory
and the math that goes along with it. Some of the proofs involve lengthy
calculations, but none are tricky or mathematically deep, because they don't
need to be. More realistically, I'd suggest some prior experience both with
actually running non-parametric regressions (at the level of,
say, Elements
of Statistical Learning Theory), and with the characteristic
concerns of non-parametric theory (say, All of Nonparametric
Statistics, or Tsybakov).
All of the major classes of regression models in common use around 2000 are
included — and that includes all the models in common use today, except
Gaussian processes. Serious statistical theorists interested in regression
have already read the book; I recommend it for those into methodology or even
applications, because it's very well done and it gives them a sense of what
lies in the background.
(Thanks to Ryan T. for persuading me to not just browse this, as I'd been
doing for a decade, but actually read it systematically.)
Mind candy: sequel
to Mr. Mercedes, but
enjoyable independently. This is because while some characters from that book
are the nominal heroes here, the really central characters are new — an
old thief and murderer, and an idealistic teenage boy, both, in different ways,
the biggest fans of an (imaginary) mid-century American novelist who seems to
interpolate
between John
Updike, J. D. Salinger
and Henry Roth; the
story is really about their rivalry for the manuscripts of his unpublished
Great American Novels.
Mind candy: fantasy novel, based on
the rise
of the Han dynasty, with added squabbling gods, "silk-punk" technology, and
glancing blows at patriarchy. I picked it up because of the quality of Liu's
translation of The Three-Body
Problem; I'd read the nigh-inevitable sequel.
In this book, Sutton is looking at what determines the level of
concentration in industries with fixed (set-up) costs, hence increasing returns
and imperfect competition, and where advertising works, in the sense that by
spending money on ads, firms can increase their sales at a given price. This
tends to lead to concentrated markets, where a small number of firms capture a
large proportion of sales. So far, so standard industrial organization. What
sets Sutton's approach apart, and makes it really distinctive, is that Sutton
realizes the equilibria of reasonable models of entry, pricing and advertising
decisions are incredibly sensitive to model details, but there
are inequalities which hold across very wide range of models. (He
went on to elaborate on this in Technology and Market Structure,
and give a programmatic statement in Marshall's Tendencies.)
Specifically, for any given size of the market, he can put a lower bound on the
degree of concentration (at equilibrium). The fixed costs of entry mean that
this lower bound initially decreases with the size of the market. (The market
has to be at least so big to pay back the cost of establishing multiple rival
plants.) But if advertising is effective, after a certain point the lower
bound actually
increases in market size — it becomes advantageous for firms to
ramp up the sunk costs of entering the market through intensive advertising.
While Sutton goes through some (comparatively) conventional econometric
exercises to do things like estimate the lower bound on concentration as a
function of the size of the market, the bulk of this book is taken up by
wonderfully detailed qualitative applications of his theory to the evolution of
concentration and corporate strategy in a wide range of food industries across
the six largest industrial economies. This is somewhat dated, having been
written in the 1980s, but still fascinating, for an admittedly-nerdy value of
fascination. Even if you don't think you care about the comparative industrial
organization of breakfast-cereal manufacturing, it's still a virtuoso
performance in melding social-scientific theory with concrete history.
Mind candy: it's hard out there for a fembot, especially when she was
designed to be an "escort" for human males and humanity, and every other
eukaryote, has been extinct for centuries. There are a lot of
science-fictional in-jokes (e.g.,
the Scalzi
museum of paleontology on Mars), and some of the revelations were things I
got long before the protagonist did. (But maybe the reader was supposed to?)
Overall, though, it works much better as a story in its own right than anything
deliberately riffing off the later works of Robert Heinlein has any right to
do.