On Strong Mixing Conditions for Stationary Gaussian Processes 论文

1960Theory of Probability and Its Applications引用 361
Analysis of environmental and stochastic processesBayesian Methods and Mixture Models

摘要

This paper considers conditions, which guarantee strong mixing of stationary random Gaussian process $\xi (t)$. It is proved, for example, that if the spectral density $f(\lambda )$ of the process $\xi(t)$ is continuous and positive (parameter t is discrete) or $f(\lambda )$ is positive and uniformly continuous, and for large $\lambda $\[ \frac{m}{{\lambda ^k }} \leqq f(\lambda ) \leqq \frac{M}{{\lambda ^{k - 1} }} \] (parameter t is continuous), then strong mixing takes place.

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