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By Siddhartha Chib, Visit Amazon's Gary Koop Page, search results, Learn about Author Central, Gary Koop, , Bill Griffiths, Dek Terrell

Illustrates the scope and variety of recent purposes, studies advances, and highlights many fascinating points of inference and computations. This paintings offers an historic assessment that describes key contributions to improvement and makes predictions for destiny instructions.

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Xi). In an attempt to measure the progress of Bayesian econometrics, Poirier (1989, 1992) reported the percentages of pages devoted to Bayesian articles in statistics and econometrics journals for the 5 year periods 1982–1988 and 1987–1991 as well as for individual years. He concludes in his 1992 paper, ‘‘The results for the 1987–1991 period support the earlier 1982–86 results. On average statistics journals have a larger Bayesian content than econometrics journals. 5%, and a representative figure for econometrics journals is 7%.

As stated in the Preface of this volume, ‘‘Professor Jaynes discusses the extended de Finetti representation theorem for both finite and infinite exchangeable sequences. The discussion and the proof are simple and concise. Jaynes also gives an example of the profound impact of this representation theorem in statistical mechanics’’ (p. 3). Thus the deductive part of de Finetti’s Bayesian approach was linked to important results in physics. Also, Jaynes, who was fond of solving paradoxes, published a 1980 article, ‘‘Marginalization and Prior Probabilities’’ in Zellner (1980) in which he showed that the Dawid– Stone–Zidek ‘‘marginalization paradox,’’ widely interpreted to reveal a defect in Bayesian methods, was based on a ‘‘subtle failure .

Another attendee at these seminars (and a Harvard colleague), John Pratt, has had a significant 32 ARNOLD ZELLNER influence on my thoughts. Though they may wish to deny it, I have discovered kindred souls in the form of James Dickey and Thomas Rothenberg’’ (pp. viii–ix). All of the above indicates that Bayesian econometricians in the early period were very concerned with and working on a wide range of topics and intent upon showing that Bayesian methods do indeed solve inductive problems better than non-Bayesian methods do.

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