COMPSTAT: Proceedings in Computational Statistics 14th by Donald B. Rubin (auth.), Prof. Jelke G. Bethlehem, Prof.

By Donald B. Rubin (auth.), Prof. Jelke G. Bethlehem, Prof. Peter G. M. van der Heijden (eds.)

This booklet includes the keynote, invited and entire contributed papers offered at COMPSTAT 2000, held in Utrecht. The papers diversity over all points of the hyperlink among statistical conception and utilized records, with designated cognizance for advancements within the region of reliable facts. The papers were completely refereed.

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London: Oxford University Press, pp. 35-60. Berger, J. O. and Mortera, J. (1995). Discussion of O'Hagan. Journal of the Royal Statistical Society, B, 57, pp. 99-138. O. R. (1996). The intrinsic Bayes factor for model selection and prediction. Journal of the American Statistical Association, 91, pp. 109-122. O. R. (1998). On Criticism and Comparison of Default Bayes Factors for Model Selection and Hypothesis Testing. In Proceedings of the Workshop on Model Selection, (Ed. W. , Bologna, pp. 1-50.

Ni but 3k such that k E Ni and j E N k . We can assign prior distributions to the 'fit (f = 0,1,2) directly, but it may be more sensible to apply a transformation, (It. ('fIt), and assign a prior to ()f.. In the one-dimensional case, the time series (1) is stationary if 1'fIl < 1. Now () = log (~) is defined on (-00,00), and hence a Gaussian prior on () would be reasonable. For the matrix H, we make a similar transformation on its entries: we choose ()f. ), f = 0,1,2. In future work, we shall consider what transformation and what prior would guarantee that the variances and covariances of the AR(l) process (3) are stationary.

K} is a partition of the sample space X and {pi, i = 1, ... , k} are their probabilities. Both the partition and their probabilities are subjectively specified by the expert. In this setting, a model Mi : {f(xIOi), 7rN (Oi)} is but a parametric representation of the "true" unknown distribution m(x). A first question arises: is 37 model Mi compatible with the expert class? i(YllJi )7rf (lJi)dlJi contained in the expert class mk(p)? The answer is clearly no since mf (x) is not well-defined as it depends on the arbi- trary constant Ci involved in 7rf (lJ i ).

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