Goodness-of-Fit Tests for Weighted Generalized Quasi-Lindley Distribution Using SRS and RSS with Applications to Real Data
نویسندگان
چکیده
This paper deals with the problem of goodness-of-fit tests (GFTs) for weighted generalized quasi-Lindley distribution (WGQLD) using ranked set sampling (RSS) and simple random (SRS) techniques. The are based on empirical function sample entropy. These include Kullback–Leibler, Kolomogorov–Smirnov, Anderson–Darling, Cramér–von Mises, Zhang, Liao, Shimokawa, Watson tests. critical values (CV) power each test obtained a simulation study by SRS RSS methods considering various sizes alternatives. A rain data is used to investigate effectiveness suggested GFTs. Based same number measured units alternatives taken into consideration in this study, it discovered that more effective than those their rivals SRS. Additionally, as size increases, GFTs’ increases.
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ژورنال
عنوان ژورنال: Axioms
سال: 2022
ISSN: ['2075-1680']
DOI: https://doi.org/10.3390/axioms11100490