Tests of Randomness and Tests of Independence
Dependogram for Kendall's tau and Spearman's rho
Function to perform multiplier bootstrap for tests of randomness or in...
Dependogram for Cramer-von Mises statistics
Dependogram for Moebius correlations
Kendall's tau and Spearman's rho statistics for testing independence b...
Dependence measures and statistics for test of independence between ra...
Kendall's tau and Spearman's rho statistics for testing randomness in ...
Dependence measures and statistics for test of randomness for a univar...
Quantile function of margins
Computes unique values, cdf and pdf
Data-driven selection of p for the test of randomness
Simulation of a AR(1) Poisson process
Simulation of a copula-based time series
Computes the Moebius Cramer-von Mises statistics for the test of indep...
Computes the Moebius Cramer-von Mises statistics for the test of rando...
Computes the Moebius Cramer-von Mises statistics for the test of rando...
Computes the Cramer-von Mises statistic Sn for the test of randomness
Computes the Kendall's taus and Spearman's rho for tests of randomness
Computes the Kendall's taus and Spearman's rho for tests of randomness
Statistics and P-values for a test of independence between random vari...
Statistics and P-values for a test of randomness for a univariate time...
Statistics and P-values for a test of randomness for a multivariate ti...
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).