In this paper, we develop tests for positive expectation dependence. The proposed tests are based on weighted Kolmogorov−Smirnov type statistics. These originate from the function valued monotonic dependence function, describing local changes of the strength of the dependence. The resulting procedure is supported by a simple and insightful graphical device. This paper presents asymptotic and simulation results for such tests. We show that an inference relying on -values and wild bootstrap allows to overcome inherent difficulties of this testing problem. Our simulations show that the new tests perform well in finite samples. A Danish fire insurance data set is examined to demonstrate the practical application of the proposed inference methods.
Accepté le :
DOI : 10.1051/ps/2017015
Keywords: Hypothesis testing, expectation dependence, Lorenz curve, monotonic dependence function, multiplier central limit theorem, wild bootstrap, Zenga curve
Ćmiel, Bogdan 1 ; Ledwina, Teresa 2
@article{PS_2017__21__536_0,
author = {\'Cmiel, Bogdan and Ledwina, Teresa},
title = {Validation of positive expectation dependence},
journal = {ESAIM: Probability and Statistics},
pages = {536--561},
year = {2017},
publisher = {EDP Sciences},
volume = {21},
doi = {10.1051/ps/2017015},
zbl = {1393.60028},
mrnumber = {3743925},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ps/2017015/}
}
TY - JOUR AU - Ćmiel, Bogdan AU - Ledwina, Teresa TI - Validation of positive expectation dependence JO - ESAIM: Probability and Statistics PY - 2017 SP - 536 EP - 561 VL - 21 PB - EDP Sciences UR - https://www.numdam.org/articles/10.1051/ps/2017015/ DO - 10.1051/ps/2017015 LA - en ID - PS_2017__21__536_0 ER -
Ćmiel, Bogdan; Ledwina, Teresa. Validation of positive expectation dependence. ESAIM: Probability and Statistics, Tome 21 (2017), pp. 536-561. doi: 10.1051/ps/2017015
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