A note on asymptotic testing theory for nonhomogeneous observations

This note shows, for ergodic and nonergodic models, how previous results on the limit distributions of the likehood ratio, score and Wald statistics can be extended under full matrix normalization. Compared to n1/2-or diagonal norming this allows, just as in asymptotic estimation theory, for more heterogeneity of the data. As a key tool the Cholesky square root is used instead of the common symmetric square root.

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Year of publication:	1988
Authors:	Fahrmeir, L.
Published in:	Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 28.1988, 2, p. 267-273
Publisher:	Elsevier
Keywords:	test statistics limit distributions full matrix normalization

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

Persistent link: https://www.econbiz.de/10008872902