On the uniqueness of maximizers of Markov-Gaussian processes
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Contributors
Abstract
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.
Details
Original language | English |
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Pages (from-to) | 71-77 |
Number of pages | 7 |
Journal | Statistics and Probability Letters |
Volume | 45 |
Issue number | 1 |
Publication status | Published - 15 Oct 1999 |
Peer-reviewed | Yes |
Keywords
ASJC Scopus subject areas
Keywords
- 60 G 17, Argmax-functional, Markov-Gaussian processes, Primary 60 G 15, Secondary 60 J 25, Uniqueness of maximizers