Bootstrapping the Portmanteau Tests in Weak Auto-Regressive Moving Average Models

DOI10.1111/rssb.12112zbMath1414.62345OpenAlexW1969584752MaRDI QIDQ5378363

Ke Zhu

Publication date: 12 June 2019

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://mpra.ub.uni-muenchen.de/61930/1/MPRA_paper_61930.pdf

zbMATH Keywords

bootstrap methodportmanteau testweighted portmanteau testpower generalized auto-regressive conditional heteroscedasticity modelsrandom-weighting approachweak auto-regressive moving average models

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Parametric hypothesis testing (62F03) Bootstrap, jackknife and other resampling methods (62F40) Markov processes: hypothesis testing (62M02)

Related Items (18)

Quasi-maximum exponential likelihood estimator and portmanteau test of double \(\operatorname{AR}(p)\) model based on \(\operatorname{Laplace}(a,b)\) ⋮ Three-step risk inference in insurance ratemaking ⋮ The ZD-GARCH model: a new way to study heteroscedasticity ⋮ A unified unit root test regardless of intercept ⋮ A unit root test for an AR(1) process with AR errors by using random weighted bootstrap ⋮ Nonparametric tests for market timing ability using daily mutual fund returns ⋮ Bootstrapping the transformed goodness-of-fit test on heavy-tailed GARCH models ⋮ Permutation testing for dependence in time series ⋮ Diagnostic tests before modeling longitudinal actuarial data ⋮ Bootstrap Inference for Garch Models by the Least Absolute Deviation Estimation ⋮ Optimal estimating function for weak location‐scale dynamic models ⋮ Test for Zero Mean of Errors In An ARMA-GGARCH Model After Using A Median Inference ⋮ Bootstrapping multivariate portmanteau tests for vector autoregressive models with weak assumptions on errors ⋮ Strict stationarity testing and GLAD estimation of double autoregressive models ⋮ Statistical inference for autoregressive models under heteroscedasticity of unknown form ⋮ Two-step risk analysis in insurance ratemaking ⋮ Non-standard inference for augmented double autoregressive models with null volatility coefficients ⋮ A MAX-CORRELATION WHITE NOISE TEST FOR WEAKLY DEPENDENT TIME SERIES

This page was built for publication: Bootstrapping the Portmanteau Tests in Weak Auto-Regressive Moving Average Models