Non-parametric test for decreasing renewal dichotomous Markov noise shock model

Sepehrifar and Yarahmadian (Stat Pap 58:1115–1124, 2017) had developed a non-parametric test for testing exponentiality against decreasing renewal dichotomous Markov noise shock model (DRDMNS) alternatives which when subjected to scrutiny under delivers. Hence, we propose a non-parametric test for t...

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Bibliographic Details
Published in:Statistical papers (Berlin, Germany) Germany), 2022-06, Vol.63 (3), p.965-982
Main Authors: Mohan, Renjith, N, Sreelakshmi, Kattumannil, Sudheesh K.
Format: Article
Language:English
Subjects:
Asymptotic properties
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Equilibrium
Finance
Hypotheses
Inequality
Insurance
Management
Mathematics and Statistics
Monte Carlo simulation
Noise
Nonparametric statistics
Operations Research/Decision Theory
Probability Theory and Stochastic Processes
Random variables
Regular Article
Statistics
Statistics for Business
Stochastic models
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Summary:Sepehrifar and Yarahmadian (Stat Pap 58:1115–1124, 2017) had developed a non-parametric test for testing exponentiality against decreasing renewal dichotomous Markov noise shock model (DRDMNS) alternatives which when subjected to scrutiny under delivers. Hence, we propose a non-parametric test for testing exponentiality against a class of distributions belonging to DRDMNS models. The asymptotic properties of the test statistic are discussed. An exact null distribution is derived and critical values with different sample sizes are obtained. The proposed test is applied to the censored data also. The results of the Monte Carlo simulations are used to further manifest the quality of the proposed test. Finally, the proposed test is illustrated using two real data sets.
ISSN:0932-5026
1613-9798
DOI:10.1007/s00362-021-01264-x