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

ISBN-10: 3642576788

ISBN-13: 9783642576782

ISBN-10: 3790813265

ISBN-13: 9783790813265

This ebook comprises the keynote, invited and whole contributed papers awarded at COMPSTAT 2000, held in Utrecht. The papers diversity over all points of the hyperlink among statistical conception and utilized records, with unique cognizance for advancements within the region of reputable facts. The papers were completely refereed.

**Read Online or Download COMPSTAT: Proceedings in Computational Statistics 14th Symposium held in Utrecht, The Netherlands, 2000 PDF**

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**Extra resources for COMPSTAT: Proceedings in Computational Statistics 14th Symposium held in Utrecht, The Netherlands, 2000**

**Example text**

This produces the so-called arithmetic intrinsic Bayes factor (AIBF), defined as L Bf/(x) = B~(x)i 2:B~(x(l)), l=l where L is the number of minimal training samples contained in the sample. Other ways of "averaging" PBFs are in Berger and Pericchi (1996, 1998). 3 Fractional Bayes factor An alternative way of avoiding the arbitrariness of choosing the training sample for which the PBF is computed, was developed by O'Hagan (1995). He replaces the correction term B~ (x(l)) in (4) with P. I(xI91 )}l/n 7r{"(9dd91 .

This leaves us with the two-way table municipality X age as our reweighting model. Using this model the resulting calibration weights will satisfy the known age distribution per municipality, which 25 under . the edit rule excludes estimates of license ownership larger than the proportion of age (~ 18). Inflating the target cross tabulation by an extra dimension seems to be a rather crude way to account for IF-THEN categorical edits, since this could easily result in unstable estimates due to insufficient degrees of freedom.

Mugglin Department of Statistics, The Ohio State University, 1958 Neil Avenue, Columbus OH 43210, USA Abstract. An infectious disease spreads through "contact" between an individual who has the disease and one who does not. However, modeling the individual-level mechanism directly requires data that would amount to observing (imperfectly) all individuals' disease statuses along their space-time lines in the region and time period of interest. More likely, data consist of spatio-temporal aggregations that give small-area counts of the number infected during successive, regular time intervals.

### COMPSTAT: Proceedings in Computational Statistics 14th Symposium held in Utrecht, The Netherlands, 2000 by Donald B. Rubin (auth.), Prof. Jelke G. Bethlehem, Prof. Peter G. M. van der Heijden (eds.)

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