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Journal ArticleDOI

Explicit expressions for moments of gamma order statistics

TLDR
In this paper, explicit closed form expressions are derived for the moments of order statistics from the gamma and generalized gamma distributions, involving the Lauricella functions of type A and type B. The usefulness of the result is illustrated through two quality control data sets.
Abstract
Explicit closed form expressions are derived for the moments of order statistics from the gamma and generalized gamma distributions. The expressions involve the Lauricella functions of type A and type B. The usefulness of the result is illustrated through two quality control data sets.

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Citations
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Journal ArticleDOI

The gamma-exponentiated exponential distribution

TL;DR: In this paper, the authors introduced a new distribution generated by gamma random variables, which includes as a special case the distribution of the lower record value from a sequence of i.i.d. random variables from a population with the exponentiated (generalized) exponential distribution.
Journal ArticleDOI

Spectral Efficiency of Mixed-ADC Massive MIMO

TL;DR: The spectral efficiency (SE) of a mixed-analog-to-digital converter (ADC) massive multiple-input multiple-output (MIMO) system in which single-antenna users communicate with a base station equipped with 1-b ADCs is studied.
Journal ArticleDOI

On The Gamma-Half Normal Distribution and Its Applications

TL;DR: In this article, a new distribution, the gamma-half normal distribution, was proposed and studied, and the shape of the distribution may be unimodal or bimodal.
Journal ArticleDOI

A study of the Gamma-Pareto (IV) distribution and its applications

TL;DR: In this article, the Gamma-Pareto (IV) distribution was proposed to model income distributions as well as a wide variety of other social and economic distributions, such as survival analysis, to model aggregate insurance claims, and the amount of rainfall accumulated in a reservoir etc.
Proceedings ArticleDOI

Parameter estimations with gamma distribution based on progressive type- I interval censoring

TL;DR: In this article, the maximum likelihood estimator and moment estimator for the two-parameter gamma distribution based on progressive type-I interval censored sample were derived using the EM algorithm and numerical method, respectively.
References
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Journal ArticleDOI

A Bootstrap Control Chart for Weibull Percentiles

TL;DR: The problem of detecting a shift of a percentile of a Weibull population in a process monitoring situation is considered and the proposed bootstrap percentile charts indicate a shift in the process percentile substantially quicker than the previously existing chart, while maintaining comparable average run lengths when the process is in control.
Journal ArticleDOI

An EWMA for Monitoring a Process Standard Deviation

TL;DR: Most applications of the exponentially weighted moving average (EWMA) for process monitoring have concentrated on the problem of detecting shifts in the mean level of a process as mentioned in this paper, but perhaps more important is detecting increases in process var..
Journal Article

Robustness to non-normality of the multivariate EWMA control chart

TL;DR: In this article, the effects of non-normality on the statistical performance of the multivariate exponentially moving average (MEWMA) control chart, and the Hotelling chi-squared chart in particular, are investigated when used in individual observations to monitor the me.
Journal ArticleDOI

Order Statistics from the Gamma Distribution

TL;DR: In this paper, the authors deal with order statistics from a gamma or χ2 (Pearson Type III) distribution and derive the modal value of an order statistic and a table of these values is given for the cases of the smallest and the largest order statistics.
Journal ArticleDOI

Computing the moments of order statistics from nonidentical random variables

TL;DR: In this article, the authors establish new representations, identities and recurrence relations of order statistics arising from general independent non-identically distributed random variables (r.v.’s), which enable one to compute all moments of all o.s. in a simple manner.
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