In nonparametric tests for serial independence the marginal distribution of the data acts as an infinite dimensional nuisance parameter. The decomposition of joint distributions in terms of a copula density and marginal densities shows that in general empirical marginals carry no information on dependence. It follows that the order of ranks is sufficient for inference, which motivates transforming the data to a pre-specified marginal distribution prior to testing. As a test statistic we use an estimator of the marginal redundancy. We numerically study the finite sample properties of the tests obtained when the data are transformed to uniform as well as normal marginals. For comparison purposes we also derive a rank-based test against local ...
We propose a test of independence of two multivariate random vectors, given a sample from the underl...
Rank correlations have found many innovative applications in the last decade. In particular,suitable...
Abstract This article reviews the nonparametric serial independence tests based on measures of diver...
In nonparametric tests for serial independence the marginal distribution of the data acts as an infi...
This article develops nonparametric tests of independence between two stochastic processes satisfyin...
Abstract. A family of linear rank statistics is proposed in order to test the independence of a time...
We propose tests for nonlinear serial dependence in time series under the null hypothesis of general...
Entropy is a classical statistical concept with appealing properties. Establishing asymptotic distri...
Intraclass rank statistics are introduced to test for independence in a bivariate population when it...
This article reviews some nonparametric serial independence tests based on measures of divergence be...
【Abstract】We propose an efcient numerical integration-based nonparametric entropy estimatorfor seria...
In the present paper we construct a new, simple, consistent and powerful test for independence by us...
In testing independence of two random variables based on rank statistics, several rank statistics su...
Thesis (Ph.D.)--University of Washington, 2021Testing independence is a fundamental statistical prob...
Optimal rank-based procedures were derived in Hallin, Ingenbleek, and Puri (1985, 1987) and Hallin a...
We propose a test of independence of two multivariate random vectors, given a sample from the underl...
Rank correlations have found many innovative applications in the last decade. In particular,suitable...
Abstract This article reviews the nonparametric serial independence tests based on measures of diver...
In nonparametric tests for serial independence the marginal distribution of the data acts as an infi...
This article develops nonparametric tests of independence between two stochastic processes satisfyin...
Abstract. A family of linear rank statistics is proposed in order to test the independence of a time...
We propose tests for nonlinear serial dependence in time series under the null hypothesis of general...
Entropy is a classical statistical concept with appealing properties. Establishing asymptotic distri...
Intraclass rank statistics are introduced to test for independence in a bivariate population when it...
This article reviews some nonparametric serial independence tests based on measures of divergence be...
【Abstract】We propose an efcient numerical integration-based nonparametric entropy estimatorfor seria...
In the present paper we construct a new, simple, consistent and powerful test for independence by us...
In testing independence of two random variables based on rank statistics, several rank statistics su...
Thesis (Ph.D.)--University of Washington, 2021Testing independence is a fundamental statistical prob...
Optimal rank-based procedures were derived in Hallin, Ingenbleek, and Puri (1985, 1987) and Hallin a...
We propose a test of independence of two multivariate random vectors, given a sample from the underl...
Rank correlations have found many innovative applications in the last decade. In particular,suitable...
Abstract This article reviews the nonparametric serial independence tests based on measures of diver...