A Generalization of the Quantile-Based Flattened Logistic Distribution

Tapan Kumar Chakrabarty () and Dreamlee Sharma ()
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Tapan Kumar Chakrabarty: North Eastern Hill University
Dreamlee Sharma: North Eastern Hill University

Annals of Data Science, 2021, vol. 8, issue 3, No 8, 603-627

Abstract: Abstract In this paper, we propose a generalization of the quantile-based flattened logistic distribution Sharma and Chakrabarty (Commun Stat Theory Methods 48(14):3643–3662, 2019. https://doi.org/10.1080/03610926.2018.1481966 ). Having described the need for such a generalization from the data science perspective, several important properties of the distribution are derived here. We show that the rth order L-moment of the distribution can be written in a closed form expression. The L-skewness ratio and the L-kurtosis ratio of the distribution have been studied in detail. The distribution is shown to posses a skewness-invariant kurtosis measure based on quantiles and L-moments. The method of matching L-moments estimation has been used to estimate the parameters of the proposed model. The model has been applied to two real-life datasets and appropriate goodness-of-fit procedures have been used to test the validity of the model.

Keywords: Flattened generalized logistic distribution; Quantile function; L-moment; Asymptotic variance; order statistics; Skewness-invariant kurtosis (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s40745-021-00322-3

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