Kernel-based portmanteau diagnostic test for ARMA time series models

DOI10.1080/23311835.2017.1296327zbMath1426.62263OpenAlexW2591082669MaRDI QIDQ5193390

Esam Mahdi

Publication date: 10 September 2019

Published in: Cogent Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/23311835.2017.1296327

zbMATH Keywords

kernel estimationgoodness-of-fitspectral densityARMA modelsdiagnostic checkweighted portmanteau test

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: hypothesis testing (62M07)

Uses Software

• R
• astsa
• WeightedPortTest
• portes

Cites Work

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• Goodness of fit tests for spectral distributions
• Time series: Theory and methods
• The log of the determinant of the autocorrelation matrix for testing goodness of fit in time series
• Improved multivariate portmanteau test
• ON WEIGHTED PORTMANTEAU TESTS FOR TIME-SERIES GOODNESS-OF-FIT
• DIAGNOSTIC CHECKING ARMA TIME SERIES MODELS USING SQUARED-RESIDUAL AUTOCORRELATIONS
• Testing for independence between two covariance stationary time series
• On a measure of lack of fit in time series models
• A proposal for a residual autocorrelation test in linear models
• A Powerful Portmanteau Test of Lack of Fit for Time Series
• Consistent Testing for Serial Correlation of Unknown Form
• New Weighted Portmanteau Statistics for Time Series Goodness of Fit Testing
• Multivariate Portmanteau Test For Autoregressive Models with Uncorrelated but Nonindependent Errors
• Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models
• Diagnostic Checking in ARMA Models With Uncorrelated Errors
• On Information and Sufficiency

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