Add to ORKGSpectral density built as Fourier transform of covariance sequence of stationary random process is determining the process characteristics and makes for analysis of it’s structure. Thus, one of the main problems in time series analysis is constructing consistent estimates of spectral density via successive, taken after equal periods of time observations of stationary random process. This article is devoted to investigation of problems dealing with application of wavelet analysis methods for solving task of spectral density nonparametric estimating of stationary random process with discrete time
In this research, we explore the applications of wavelet theory in nonparametric regression and dens...
The coherence function measures the correlation between a pair of random processes in the frequency ...
A spectral density matrix estimator for stationary stochastic vector processes is studied. As the du...
Spectral density built as Fourier transform of covariance sequence of stationary random process is ...
The main task of this research work is applying techniques of wavelet analysis in spectral analysis...
International audienceIn numerous applications data are observed at random times and an estimated gr...
We study the problem of estimating the spectral density of a stationary Gaussian time series. We use...
In the present paper we consider nonlinear wavelet estimators of the spectral density f of a zero me...
International audienceFrom a wavelet analysis, one derives a nonparametrical estimator for the spect...
In this paper we give the main uses of wavelets in statistics, with emphasis in time series analysis...
In this paper, we study the problem of adaptive estimation of the spectral density of a stationary G...
We suggest a new approach to wavelet threshold estimation of spectral densities of stationary time s...
The class of locally stationary wavelet processes is a wavelet-based model for covariance nonstation...
This thesis deals with the applications of wavelet theory to time series data. We first focus on sta...
International audienceFrom a wavelet analysis, one derives a nonparametrical estimator for the spect...
In this research, we explore the applications of wavelet theory in nonparametric regression and dens...
The coherence function measures the correlation between a pair of random processes in the frequency ...
A spectral density matrix estimator for stationary stochastic vector processes is studied. As the du...
Spectral density built as Fourier transform of covariance sequence of stationary random process is ...
The main task of this research work is applying techniques of wavelet analysis in spectral analysis...
International audienceIn numerous applications data are observed at random times and an estimated gr...
We study the problem of estimating the spectral density of a stationary Gaussian time series. We use...
In the present paper we consider nonlinear wavelet estimators of the spectral density f of a zero me...
International audienceFrom a wavelet analysis, one derives a nonparametrical estimator for the spect...
In this paper we give the main uses of wavelets in statistics, with emphasis in time series analysis...
In this paper, we study the problem of adaptive estimation of the spectral density of a stationary G...
We suggest a new approach to wavelet threshold estimation of spectral densities of stationary time s...
The class of locally stationary wavelet processes is a wavelet-based model for covariance nonstation...
This thesis deals with the applications of wavelet theory to time series data. We first focus on sta...
International audienceFrom a wavelet analysis, one derives a nonparametrical estimator for the spect...
In this research, we explore the applications of wavelet theory in nonparametric regression and dens...
The coherence function measures the correlation between a pair of random processes in the frequency ...
A spectral density matrix estimator for stationary stochastic vector processes is studied. As the du...