Energy Statistic-Based Goodness-of-Fit Test for the Lindley Distribution with Application to Lifetime Data

Joseph Njuki () and Ryan Avallone
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Joseph Njuki: Department of Mathematics and Statistics, Coastal Carolina University, Conway, SC 29526, USA
Ryan Avallone: Department of Mathematics and Statistics, Coastal Carolina University, Conway, SC 29526, USA

Stats, 2025, vol. 8, issue 4, 1-14

Abstract: In this article, we propose a goodness-of-fit test for a one-parameter Lindley distribution based on energy statistics. The Lindley distribution has been widely used in reliability studies and survival analysis, especially in applied sciences. The proposed test procedure is simple and more powerful against general alternatives. Under different settings, Monte Carlo simulations show that the proposed test is able to be well controlled for any given nominal levels. In terms of power, the proposed test outperforms other existing similar methods in different settings. We then apply the proposed test to real-life datasets to demonstrate its competitiveness and usefulness.

Keywords: Lindley distribution; goodness-of-fit; energy statistics; empirical distribution function (EDF) tests; exponential distribution (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jstats:v:8:y:2025:i:4:p:87-:d:1759402

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