Functions for testing randomness for a univariate time series with arbitrary distribution (discrete, continuous, mixture of both types) and for testing independence between random variables with arbitrary distributions. The test statistics are based on the multilinear empirical copula and multipliers are used to compute P-values. The test of independence between random variables appeared in Genest, Nešlehová, Rémillard & Murphy (2019) and the test of randomness appeared in Nasri (2022).
Version: 1.2.0 Depends: R (≥ 3.5.0), doParallel, parallel, foreach, stats, copula Imports: ggplot2, survey Published: 2024-02-14 DOI: 10.32614/CRAN.package.MixedIndTests Author: Bouchra R. Nasri [aut, cre, cph], Bruno N Remillard [aut], Johanna G Neslehova [aut], Christian Genest [aut] Maintainer: Bouchra R. Nasri <bouchra.nasri at umontreal.ca> License: GPL-3 NeedsCompilation: yes CRAN checks: MixedIndTests results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=MixedIndTests to link to this page.
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