A wavelet-based time-varying autoregressive model for non-stationary and irregular time series

DOI10.1080/02664763.2012.702267OpenAlexW1967489153MaRDI QIDQ5127101

F. R. Momo, Rogério F. Porto, Gladys E. Salcedo, S. Y. Roa

Publication date: 21 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2012.702267

zbMATH Keywords

waveletsmultiresolution analysislocally stationary processesautoregressive modelirregularly spaced time series

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Wavelet fuzzy hybrid model for physico-financial signals

Uses Software

• wavethresh
• astsa

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Exponential smoothing for irregular data.
• Wavelet based time-varying vector autoregressive modelling
• Wavelets on the interval and fast wavelet transforms
• Minimax estimation via wavelet shrinkage
• Wavelet shrinkage for nonequispaced samples
• Nonlinear wavelet estimation of time-varying autoregressive processes
• Maximum Likelihood Fitting of ARMA Models to Time Series with Missing Observations
• Ten Lectures on Wavelets
• Functional-Coefficient Regression Models for Nonlinear Time Series
• Time-domain estimation of time-varying linear systems
• Functional-Coefficient Autoregressive Models
• Holt-Winters Method with Missing Observations

This page was built for publication: A wavelet-based time-varying autoregressive model for non-stationary and irregular time series