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    <title>Notebooks   </title>
    <link>http://bactra.org/notebooks</link>
    <description>Cosma's Notebooks</description>
    <language>en</language>

  <item>
    <title>Maximum Entropy Methods</title>
    <link>http://bactra.org/notebooks/2009/04/10#max-ent</link>
    <description>
&lt;P&gt;It's heresy, but I really don't believe in the maximum entropy principle.
Or at least: this is heresy among physicist who are interested in their
intersection of their subject with &lt;a
href=&quot;physics-computation-information.html&quot;&gt;information theory and
computation&lt;/a&gt;, as I am.

&lt;P&gt;Now, of course I believe that states of thermodynamic equilibrium are states
of maximum entropy.  I Am Not a Crank, or at least not that much of one.  But I
don't believe that this is due to some general fact about inductive inference
or incomplete information, which is the view propagated by the late, great
E. T. Jaynes.  I guess I should explain what I do believe about equilibrium
thermodynamics and statistical mechanics, and then what it is that I don't
believe about entropy maximization.  But another time.

&lt;P&gt;See also:
	&lt;a href=&quot;stat-mech.html&quot;&gt;Statistical Mechanics&lt;/a&gt;;
	&lt;a href=&quot;statistics.html&quot;&gt;Statistics&lt;/a&gt;;
	&lt;a href=&quot;tsallis.html&quot;&gt;Tsallis Statistics&lt;/a&gt;

&lt;ul&gt;Recommended:
	&lt;li&gt;I. Csisz&amp;aacute;r, &quot;Maxent, Mathematics, and Information Theory&quot;,
pp. 35--50 in Kenneth M. Hanson and Richards N. Silver (eds.), &lt;cite&gt;Maximum
Entropy and Bayesian Methods: Proceedings of the Fifteenth International
Workshop on Maximum Entropy and Bayesian Methods&lt;/cite&gt;
	&lt;li&gt;E. T. Jaynes
		&lt;ul&gt;
		&lt;li&gt;&quot;Information Theory and Statistical Mechanics I,&quot; 
&lt;cite&gt;Physical Review&lt;/cite&gt; &lt;strong&gt;106&lt;/strong&gt; (1957): 620--630
		&lt;li&gt;&quot;Information Theory and Statistical Mechanics II,&quot;
&lt;cite&gt;Physical Review&lt;/cite&gt; &lt;strong&gt;108&lt;/strong&gt; (1957): 171--190
		&lt;li&gt;&lt;cite&gt;Papers on Probability, Statistics, and Statistical
Physics&lt;/cite&gt; [Reprints both those papers, with many other important ones by
Jaynes]
		&lt;/ul&gt;
	&lt;li&gt;&lt;a href=&quot;http://www.stat.cmu.edu/~kass/&quot;&gt;Robert E. Kass&lt;/a&gt;
and &lt;a href=&quot;http://www.stat.cmu.edu/~larry/&quot;&gt;Larry Wasserman&lt;/a&gt;, &quot;The
Selection of Prior Distributions by Formal Rules&quot;, &lt;cite&gt;Journal of the
American Statistical Association&lt;/cite&gt; &lt;strong&gt;91&lt;/strong&gt; (1996): 1343--1370
[&lt;a href=&quot;http://www.stat.cmu.edu/~kass/papers/rules.pdf&quot;&gt;PDF reprint&lt;/a&gt;]
	&lt;li&gt;Teddy Seidenfeld [Demonstrations that max-ent methods are, in fact,
plagued by the same problems as the old Principle of Insufficient Reason, and
not consistent with Bayesian inference]
		&lt;ul&gt;
		&lt;li&gt;&quot;Why I Am Not an Objective Bayesian: Some Reflections
Prompted by Rosenkrantz&quot;, &lt;cite&gt;Theory and Decision&lt;/cite&gt; &lt;strong&gt;11&lt;/strong&gt;
(1979): 413--440
		&lt;li&gt;&quot;Entropy and Uncertainty&quot;, pp. 259--287 in I. B. MacNeill
and G. J. Umphrey (eds.), &lt;cite&gt;Foundations of Statistical Inference&lt;/cite&gt;
(1987)
		&lt;/ul&gt;
	&lt;li&gt;Jos Uffink
		&lt;ul&gt;
		&lt;li&gt;&quot;Can the Maximum Entropy Principle be explained as a
Consistency Requirement?&quot;, &lt;cite&gt;Studies in History and Philosophy of Modern
Physics&lt;/cite&gt; &lt;strong&gt;26B&lt;/strong&gt; (1995): 223-261 [&lt;a
href=&quot;http://www.phys.uu.nl/~wwwgrnsl/jos/mepabst/mepabst.html&quot;&gt;Abstract, with
links to PDF and PS&lt;/a&gt;]
		&lt;li&gt;&quot;The Constraint Rule of the Maximum Entropy
Principle,&quot; &lt;cite&gt;Studies in History and Philosophy of Modern
Physics&lt;/cite&gt; &lt;strong&gt;27&lt;/strong&gt; (1996): 47--79 [I can describe my reaction
to this very simply: Word.  &lt;a
href=&quot;Http://www.phys.uu.nl/~wwwgrnsl/jos/mep2def/mep2def.html&quot;&gt;Abstract, with
links to PDF and PS&lt;/a&gt;]
		&lt;/ul&gt;
	&lt;/ul&gt;

&lt;ul&gt;Modesty forbids me to recommend:
	&lt;li&gt;CRS, &quot;The Backwards Arrow of Time of the Consistently Bayesian
Statistical Mechanic&quot;, &lt;a
href=&quot;http://arxiv.org/abs/cond-mat/0410063&quot;&gt;cond-mat/0410063&lt;/a&gt;
	&lt;/ul&gt;

&lt;ul&gt;To read (thanks to Edward Burns for recommendations):
	&lt;li&gt;Ariel Caticha, &quot;Questions, Relevance and Relative Entropy&quot;, &lt;a
href=&quot;http://arxiv.org/abs/cond-mat/0409175&quot;&gt;cond-mat/0409175&lt;/a&gt;
	&lt;li&gt;P. Dias and A. Shimony, &quot;A Critique of Jaynes' Maximum Entropy
Principle,&quot; &lt;cite&gt;Advances in Applied Mathematics&lt;/cite&gt; &lt;strong&gt;2&lt;/strong&gt;
(1981): 172--211
	&lt;li&gt;K. Friedman, and A. Shimony, &quot;Jaynes' Maximum Entropy Prescription
and Probability Theory,&quot; &lt;cite&gt;Journal of Statistical
Physics&lt;/cite&gt; &lt;strong&gt;3&lt;/strong&gt; (1971): 381-384.
	&lt;li&gt;Peter Grunwald and A. Philip Dawid, &quot;Game Theory, Maximum Entropy,
Minimum Discrepancy and Robust Bayesian Decision
Theory&quot;, &lt;a href=&quot;http://dx.doi.org/10.1214/009053604000000553&quot;&gt;&lt;cite&gt;Annals of
Statistics&lt;/cite&gt; &lt;strong&gt;32&lt;/strong&gt; (2004): 1367--1433&lt;/a&gt;
	&lt;li&gt;Patrick Haffner, Steven Phillips and Rob Schapire, &quot;Efficient
Multiclass Implementations of L1-Regularized Maximum Entropy&quot;, &lt;a
href=&quot;http://arxiv.org/abs/cs.LG/0506101&quot;&gt;cs.LG/0506101&lt;/a&gt;
	&lt;li&gt;Prakash Ishwar and Pierre Moulin, &quot;On the existence and
characterization of the maxent distribution under general moment inequality
constraints&quot;, &lt;a href=&quot;http://arxiv.org/abs/cs.IT/0506013&quot;&gt;cs.IT/0506013&lt;/a&gt;
= &lt;a href=&quot;http://dx.doi.org/10.1109/TIT.2005.853317&quot;&gt;&lt;cite&gt;IEEE Transactions
on Information Theory&lt;/cite&gt; &lt;strong&gt;51&lt;/strong&gt; (2005): 3322--3333&lt;/a&gt; [&quot;A
broad set of sufficient conditions that guarantees the existence of the maximum
entropy (maxent) distribution consistent with specified bounds on certain
generalized moments is derived. Most results in the literature are either
focused on the minimum cross-entropy distribution or apply only to
distributions with a bounded-volume support or address only equality
constraints. The results of this work hold for general moment inequality
constraints for probability distributions with possibly unbounded support, and
the technical conditions are explicitly on the underlying generalized moment
functions.&quot;]
	&lt;li&gt;Oliver Johnson and Christophe Vignat, &quot;Some results concerning
maximum Renyi entropy distributions&quot;, &lt;a
href=&quot;http://arxiv.org/abs/math.PR/0507400&quot;&gt;math.PR/0507400&lt;/a&gt;
	&lt;li&gt;Jill North, &quot;Symmetry and Probability&quot;, &lt;a
href=&quot;http://philsci-archive.pitt.edu/archive/00002978/&quot;&gt;phil-sci/2978&lt;/a&gt; [I
heard Prof. North talk about this at PSA 2006, and it sounded good, but I need
to read the details.]
	&lt;/ul&gt;
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