Cross validation for locally stationary processes
نویسندگان
چکیده
منابع مشابه
Second Order Properties of Locally Stationary Processes
In this paper we investigate an optimal property of the maximum likelihood estimator of Gaussian locally stationary processes by the second order approximation. In the case where the model is correctly specified, it is shown that appropriate modifications of the maximum likelihood estimator for Gaussian locally stationary processes is second order asymptotically efficient. We discuss second ord...
متن کاملForecasting Using Locally Stationary Wavelet Processes
Locally stationary wavelet (LSW) processes, built on non-decimated wavelets, can be used to analyze and forecast non-stationary time series. They have been proved useful in the analysis of financial data. In this paper we first carry out a sensitivity analysis, then propose some practical guidelines for choosing the wavelet bases for these processes. The existing forecasting algorithm is found ...
متن کاملSpectral decomposition of locally stationary random processes
The notion of a locally stationary process is introduced by Silverman in [ l j . This is a new kind of a random process generalizing the notion of a weakly station ary process. Let {x(t)}, teR1bsa random process, generally complex, with vanishing mean value and finite covariance function R(s, t) = E{x(s) x(r)} on Wj x Mu where x(t) is the complex conjugate to x(r). The author of [ l j says tha...
متن کاملEmpirical Likelihood Approach for Non-Gaussian Locally Stationary Processes
An application of empirical likelihood method to non-Gaussian locally stationary processes is presented. Based on the central limit theorem for locally stationary processes, we calculate the asymptotic distribution of empirical likelihood ratio statistics. It is shown that empirical likelihood method enables us to make inference on various important indices in time series analysis. Furthermore,...
متن کاملGeneralized Information Criteria in Model Selection for Locally Stationary Processes
The problem of fitting a parametric model of time series with time varying parameters attracts our attention. We evaluate a goodness of time varying spectral models from an information theoretic point of view. We propose model selection criteria for locally stationary processes based on nonlinear functionals of a time varying spectral density without assuming that the true time varying spectral...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2019
ISSN: 0090-5364
DOI: 10.1214/18-aos1743