Schätzen der Kovarianzdichte stationärer Punktprozesse aus Zählungen.
Siegel's test for periodic components in multiple time series and its application in engineering practice
Some New Time Series Results.
Some results on the spectral analysis of nonstationary time series.
Spectral analysis of ARMA processes by Prony's method
Spectral density estimation for -adic stationary processes
Spectral density estimation for stationary stable random fields
We consider a stationary symmetric stable bidimensional process with discrete time, having the spectral representation (1.1). We consider a general case where the spectral measure is assumed to be the sum of an absolutely continuous measure, a discrete measure of finite order and a finite number of absolutely continuous measures on several lines. We estimate the density of the absolutely continuous measure and the density on the lines.
Spectrum of randomly sampled multivariate ARMA models
The paper is devoted to the spectrum of multivariate randomly sampled autoregressive moving-average (ARMA) models. We determine precisely the spectrum numerator coefficients of the randomly sampled ARMA models. We give results when the non-zero poles of the initial ARMA model are simple. We first prove the results when the probability generating function of the random sampling law is injective, then we precise the results when it is not injective.
Statistical applications for equivariant matrices.
Statistical estimation of higher-order spectral densities by means of general tapering
Given a realization on a finite interval of a continuous-time stationary process, we construct estimators for higher order spectral densities. Tapering and shift-in-time methods are used to build estimators which are asymptotically unbiased and consistent for all admissible values of the argument. Asymptotic results for the fourth-order densities are given. Detailed attention is paid to the nth order case.