Details

Autor(en) / Beteiligte

• Beran, R.
• Millar, P. W.

Titel

A Stochastic Minimum Distance Test for Multivariate Parametric Models

Ist Teil von

• The Annals of statistics, 1989-03, Vol.17 (1), p.125-140

Ort / Verlag

Hayward, CA: Institute of Mathematical Statistics

Erscheinungsjahr

1989

Quelle

Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals

Beschreibungen/Notizen

• Stochastic procedures are randomized statistical procedures which are functions of the observed sample and of one or more artificially constructed auxiliary samples. As the size of the auxiliary samples increases, a stochastic procedure becomes nearly nonrandomized. The stochastic test of this paper arises as a numerically feasible approximation to a natural minimum distance goodness-of-fit test for multivariate parametric models. The distance being minimized here is the half-space metric for probabilities on a Euclidean space. It is shown that the various approximations used in constructing the stochastic test and its critical values do not detract from its first-order asymptotic performance.