Accurate Parametric Inference for Small Samples

Details Accurate Parametric Inference for Small Samples Accurate Parametric Inference for Small Samples

2009-06-22

arxiv.org/abs/0906.3935v1

Statistical Science 2008, Vol. 23, No. 4, 465-484

Statistics

Methodology

Published in at http://dx.doi.org/10.1214/08-STS273 the Statistical Science (http://www.imstat.org/sts/) by the Institute of M

Scientific paper

10.1214/08-STS273

We outline how modern likelihood theory, which provides essentially exact inferences in a variety of parametric statistical problems, may routinely be applied in practice. Although the likelihood procedures are based on analytical asymptotic approximations, the focus of this paper is not on theory but on implementation and applications. Numerical illustrations are given for logistic regression, nonlinear models, and linear non-normal models, and we describe a sampling approach for the third of these classes. In the case of logistic regression, we argue that approximations are often more appropriate than `exact' procedures, even when these exist.

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