TY  - JOUR
A1  - Gaigall, Daniel
T1  - On the applicability of several tests to models with not identically distributed random effects
T2  - Statistics : A Journal of Theoretical and Applied Statistics
N2  - We consider Kolmogorov–Smirnov and Cramér–von-Mises type tests for testing central symmetry, exchangeability, and independence. In the standard case, the tests are intended for the application to independent and identically distributed data with unknown distribution. The tests are available for multivariate data and bootstrap procedures are suitable to obtain critical values. We discuss the applicability of the tests to random effects models, where the random effects are independent but not necessarily identically distributed and with possibly unknown distributions. Theoretical results show the adequacy of the tests in this situation. The quality of the tests in models with random effects is investigated by simulations. Empirical results obtained confirm the theoretical findings. A real data example illustrates the application.
KW  - central symmetry test
KW  - exchangeability test
KW  - independence test
KW  - random effects
KW  - not identically distributed
Y1  - 2023
UR  - https://opus.bibliothek.fh-aachen.de/opus4/frontdoor/index/index/docId/10590
SN  - 0323-3944
SN  - 1029-4910
VL  - 57
PB  - Taylor & Francis
CY  - London
ER  -