TY  - JOUR
A1  - Baringhaus, Ludwig
A1  - Gaigall, Daniel
T1  - On an independence test approach to the goodness-of-fit problem
JF  - Journal of Multivariate Analysis
N2  - Let X₁,…,Xₙ be independent and identically distributed random variables with distribution F. Assuming that there are measurable functions f:R²→R and g:R²→R characterizing a family F of distributions on the Borel sets of R in the way that the random variables f(X₁,X₂),g(X₁,X₂) are independent, if and only if F∈F, we propose to treat the testing problem H:F∈F,K:F∉F by applying a consistent nonparametric independence test to the bivariate sample variables (f(Xᵢ,Xⱼ),g(Xᵢ,Xⱼ)),1⩽i,j⩽n,i≠j. A parametric bootstrap procedure needed to get critical values is shown to work. The consistency of the test is discussed. The power performance of the procedure is compared with that of the classical tests of Kolmogorov–Smirnov and Cramér–von Mises in the special cases where F is the family of gamma distributions or the family of inverse Gaussian distributions.
KW  - Goodness-of-fit test
KW  - Independence test
KW  - Parametric bootstrap
KW  - Vapnik–Čhervonenkis class
KW  - Gamma distribution
Y1  - 2015
U6  - http://dx.doi.org/10.1016/j.jmva.2015.05.013
SN  - 0047-259X
VL  - 2015
IS  - 140
SP  - 193
EP  - 208
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Gaigall, Daniel
A1  - Gerstenberg, Julian
A1  - Trinh, Thi Thu Ha
T1  - Empirical process of concomitants for partly categorial data and applications in statistics
JF  - Bernoulli
N2  - On the basis of independent and identically distributed bivariate random vectors, where the components are categorial and continuous variables, respectively, the related concomitants, also called induced order statistic, are considered. The main theoretical result is a functional central limit theorem for the empirical process of the concomitants in a triangular array setting. A natural application is hypothesis testing. An independence test and a two-sample test are investigated in detail. The fairly general setting enables limit results under local alternatives and bootstrap samples. For the comparison with existing tests from the literature simulation studies are conducted. The empirical results obtained confirm the theoretical findings.
KW  - bootstrap
KW  - Categorial variable
KW  - Concomitant
KW  - Empirical process
KW  - Independence test
Y1  - 2022
U6  - http://dx.doi.org/10.3150/21-BEJ1367
SN  - 1573-9759
VL  - 28
IS  - 2
SP  - 803
EP  - 829
PB  - International Statistical Institute
CY  - Den Haag, NL
ER  -