Vaisakh KM (Research Scholar)http://starc.stthomas.ac.in:8080/xmlui/xmlui/handle/123456789/4342026-04-20T13:52:01Z2026-04-20T13:52:01ZGoodness-of-fit tests for inverse Gaussian distribution in the presence and absence of censoringXavier, ThomasVaisakh, K. M.Sreedevi, E. Phttp://starc.stthomas.ac.in:8080/xmlui/xmlui/handle/123456789/4472025-02-12T06:01:26Z2024-12-30T00:00:00ZGoodness-of-fit tests for inverse Gaussian distribution in the presence and absence of censoring
Xavier, Thomas; Vaisakh, K. M.; Sreedevi, E. P
In this article, we use the fixed point characterization for inverse
Gaussian distribution to develop goodness of fit tests for the same.
First, we propose a test for inverse Gaussian distribution when the
data is complete. We then discuss, how the test procedure can
be modified to incorporate right-censored observations. We use
U-statistics theory to develop the test statistic. The large sample
behaviour of the proposed test statistics for both uncensored and
censored data are studied. We conduct extensive Monte Carlo simulation studies to validate the finite sample behaviour of the proposed
tests. The practical usefulness of the tests is illustrated using real data
sets. We also propose a new jackknife empirical likelihood ratio test
for the inverse Gaussian distribution with unit parameters.
2024-12-30T00:00:00Z