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Estimation of linear models with nequal restrictions
Author(s) -
Moors J. J. A.,
Houwelingen J. C.
Publication year - 1993
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/j.1467-9574.1993.tb01416.x
Subject(s) - mathematics , estimator , property (philosophy) , linear regression , set (abstract data type) , regression , regression analysis , space (punctuation) , statistics , computer science , philosophy , epistemology , programming language , operating system
Inequality constrained regression involves the notion of a truncated parameter space, which was studied extensively by Moors (1985). His general results are extended here and applied to linear models. Using the invariance principle, for every observation x a set V x is defined with the property that estimators taking values in V x (with positive probability) are inadmissible. One of the main conclusions is that the usual estimators in inequality constrained regression are inadmissible; a method to obtain better estimators is indicated.