Symmetry and Unimodality in Linear Inference

Distribution-free results beyond Gauss-Markov theory are found under weak assumptions regarding the errors. Symmetry, unimodality, and location-scale families are studied in estimation; nonstandard versions of Gauss-Markov results are given; and distribution-free confidence sets are tightened under symmetry and unimodality of errors. Normal-theory approximate tests are seen to exhibit monotone power in certain classes of symmetric unimodal errors.

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Year of publication:	1997
Authors:	Jensen, D. R.
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 60.1997, 2, p. 188-202
Publisher:	Elsevier
Keywords:	symmetry under reflections unimodal mixtures location median modal-unbiasedness Gauss-Markov theory tightened confidence bounds

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005221466