Asymptotic inference of the ARMA model with time-functional variance noises

Cites Work

Adaptive estimation of autoregressive models with time-varying variances
Corrected portmanteau tests for VAR models with time-varying variance
Self-weighted and local quasi-maximum likelihood estimators for ARMA-GARCH/IGARCH models
Testing for unit roots in time series models with non-stationary volatility
Adaptive estimation of vector autoregressive models with time-varying variance: application to testing linear causality in mean
Empirical spectral processes for locally stationary time series
Global self-weighted and local quasi-maximum exponential likelihood estimators for ARMA-GARCH/IGARCH models
Testing for co-integration in vector autoregressions with non-stationary volatility
Bootstrapping autoregressions with conditional heteroskedasticity of unknown form
Time series: Theory and methods
Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes
Generalized autoregressive conditional heteroscedasticity
Adaptive estimation of AR(\(\infty\)) models with time-varying variances
Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model
Statistical inference for autoregressive models under heteroscedasticity of unknown form
Unit Root Tests under Time-Varying Variances
A Haar–Fisz technique for locally stationary volatility estimation
Inference in Autoregression under Heteroskedasticity
Autoregressive Order Identification for VAR Models with Non Constant Variance
BOOTSTRAP UNIT ROOT TESTS FOR TIME SERIES WITH NONSTATIONARY VOLATILITY
Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
Introduction to Time Series and Forecasting
Testing Second-Order Dynamics for Autoregressive Processes in Presence of Time-Varying Variance
Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models
Analysis of Financial Time Series

This page was built for publication: Asymptotic inference of the ARMA model with time-functional variance noises