Reducing non-stationary stochastic processes to stationarity by a time deformation

DOI10.1016/S0167-7152(98)00278-8zbMath0968.60030MaRDI QIDQ1962235

Olivier Perrin, Rachid Senoussi

Publication date: 2 July 2000

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

zbMATH Keywords

correlation functionstationary processtime transformationsecond order process

Mathematics Subject Classification ID

Stationary stochastic processes (60G10) General second-order stochastic processes (60G12)

Related Items (15)

Quadratic variation for Gaussian processes and application to time deformation ⋮ Point pattern analysis of spatial deformation and blurring effects on exceedances ⋮ On a time deformation reducing nonstationary stochastic processes to local stationarity ⋮ High resolution simulation of nonstationary Gaussian random fields ⋮ Spectral density estimation from random sampling for multiplicative stationary processes ⋮ Riesz-based orientation of localizable Gaussian fields ⋮ Reduction problems and deformation approaches to nonstationary covariance functions over spheres ⋮ Time changes and stationarity issues for extended scalar autoregressive models ⋮ Filling the gap between Continuous and Discrete Time Dynamics of Autoregressive Processes ⋮ Estimating deformations of stationary processes ⋮ On the non-reducibility of non-stationary correlation functions to stationary ones under a class of mean-operator transformations ⋮ Self-Similarity and Lamperti Transformation for Random Fields ⋮ G-filtering nonstationary time series ⋮ Reducing non-stationary random fields to stationarity and isotropy using a space deformation ⋮ Gaussian multi-self-similar random fields with distinct stationary properties of their rectangular increments

Cites Work

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