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On the uniqueness of maximizers of Markov-Gaussian processes

Let Y be a nonconstant Markov-Gaussian process with almost sure continuous sample functions. We show that with probability one the original process Y and the reflected process Y in each case attain their maximal value at precisely one point. Almost sure uniqueness of maximizers of stochastic processes plays an important role when deriving the limit distribution of M-estimators.
Year of publication:
1999
Authors: Ferger, Dietmar
Published in:
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 45.1999, 1, p. 71-77
Publisher: Elsevier
Keywords: Markov-Gaussian processes Uniqueness of maximizers Argmax-functional
Type of publication: Article
Source:
Persistent link: https://www.econbiz.de/10005259078
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