日期精度：到日 3 篇 · 到月 0 篇 · 到年 0 篇
谱密度估计的筛方法
We suggest a sieve for the estimation of the spectral density of a Gaussian stationary stochastic process. In contrast to the standard periodogram-based estimates this one aims at exploiting the full Gaussian nature of the process.
不同谱的两个高斯过程之间的大样本判别
We study the probability of error asymptotically for testing one Gaussian stochastic process against another when the mean vectors are zero and we have the choice between two given covariance matrices. It is shown that under certain conditions the probabilities of error form asymptotically a geometric progression with a ratio that is derived. The approach employs Laplace's method of approximating integrals and does not appeal to Fourier analysis; in this sense it can be said…
谱估计中的带宽与方差
SUMMARY This paper deals with the uncertainty principle that governs the behaviour of bandwidth and variance in the estimation of the spectrum of a stationary stochastic process. Lomnicki and Zaremba (1957) have tried to show that this principle is not valid. It will be shown below that their reasoning is not correct. Further it will be shown, that not only is the uncertainty principle correct as it was originally stated, but that it can be extended in various directions.…