On adaptive covariance and spectrum estimation of locally stationary multivariate processes

DOI10.1016/j.automatica.2017.04.033zbMath1376.93102OpenAlexW2610667023MaRDI QIDQ2409117

Marcin Ciołek, Yoshinobu Kajikawa, Maciej Niedźwiecki

Publication date: 11 October 2017

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2017.04.033

zbMATH Keywords

model order selectionidentification of nonstationary processesdetermination of estimation bandwidth

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Adaptive control/observation systems (93C40) Estimation and detection in stochastic control theory (93E10)

Related Items (2)

A new look at the statistical identification of nonstationary systems ⋮ ADAPTATION FOR NONPARAMETRIC ESTIMATORS OF LOCALLY STATIONARY PROCESSES

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• On noncausal weighted least squares identification of nonstationary stochastic systems
• On covariance function tests used in system identification
• Easy recipes for cooperative smoothing
• Modeling by shortest data description
• Convergence of weighted sums of tight random elements
• Estimating the dimension of a model
• Fitting time series models to nonstationary processes
• On spatially adaptive estimation of nonparametric regression
• Autoregressive model fitting for control
• Local inference for locally stationary time series based on the empirical spectral measure
• On the localized estimators and generalized Akaike's criteria
• Bayesian-like autoregressive spectrum estimation in the case of unknown process order
• Nonasymptotic results for finite-memory WLS filters
• Statistical Reconstruction of Multivariate Time Series
• On the Optimal Segment Length for Parameter Estimates for Locally Stationary Time Series
• Locally Adaptive Cooperative Kalman Smoothing and Its Application to Identification of Nonstationary Stochastic Systems
• Model Selection, Transformations and Variance Estimation in Nonlinear Regression
• Time and Spectral Domain Relative Entropy: A New Approach to Multivariate Spectral Estimation
• New Approach to Noncausal Identification of Nonstationary Stochastic FIR Systems Subject to Both Smooth and Abrupt Parameter Changes
• Performance Analysis of the Adaptive Algorithm for Bias-to-Variance Tradeoff
• A new look at the statistical model identification

This page was built for publication: On adaptive covariance and spectrum estimation of locally stationary multivariate processes