TESTING SERIAL INDEPENDENCE USING THE SAMPLE DISTRIBUTION FUNCTION

DOI10.1111/j.1467-9892.1996.tb00276.xzbMath0854.62047OpenAlexW2017365027MaRDI QIDQ4892826

Miguel A. Delgado

Publication date: 19 January 1997

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10016/2429

zbMATH Keywords

Monte Carlo experimentcritical valuesserial dependenceCramer-von Mises statisticergodic alternativesHoeffding-Blum-Kiefer-Rosenblatt empirical processmultivariate sample distributionrandom permutation testrandom walk hypothesis of exchange rate returnsserial independence tests

Mathematics Subject Classification ID

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

Related Items (21)

Testing for serial independence of panel errors ⋮ A non-parametric independence test using permutation entropy ⋮ A Statistical Method for the Determination of the Appropriate Order in a General Class of Time Series Models ⋮ Tests of serial independence based on Kendall's process ⋮ Tests of independence and randomness based on the empirical copula process ⋮ DIAGNOSTIC CHECKING FOR THE ADEQUACY OF NONLINEAR TIME SERIES MODELS ⋮ Multivariate specification tests based on a dynamic Rosenblatt transform ⋮ Testing Conditional Independence Restrictions ⋮ Empirical processes for infinite variance autoregressive models ⋮ Tests of serial independence for continuous multivariate time series based on a Möbius decomposition of the independence empirical copula process ⋮ Measures of Dependence and Tests of Independence ⋮ Serial independence tests for innovations of conditional mean and variance models ⋮ Testing serial independence via density-based measures of divergence ⋮ Testing spatial randomness based on empirical distribution function: a study on lattice data ⋮ A nonparametric test of serial independence for time series and residuals ⋮ Generalized runs tests for the IID hypothesis ⋮ Non parametric portmanteau tests for detecting non linearities in high dimensions ⋮ A-dependence statistics for mutual and serial independence of categorical variables ⋮ Entropy and predictability of stock market returns. ⋮ Diagnostic Tests for Innovations of ARMA Models Using Empirical Processes of Residuals ⋮ A test for independence of two stationary infinite order autoregressive processes

Cites Work

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• Bootstrap and randomization tests of some nonparametric hypotheses
• The Rank Version of von Neumann's Ratio Test for Randomness
• Testing for randomness against autocorrelation: Alternative tests
• A nonparametric test of serial independence based on the empirical distribution function
• Distribution Free Tests of Independence Based on the Sample Distribution Function
• Consistent Nonparametric Entropy-Based Testing
• A Non-Parametric Test of Independence

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