Progressively Censored Data from The Weibull Gamma Distribution Moments and Estimation

Mahmoud, M. A. W.; Moshref, M.E.; Yhiea, N. M.; Mohamed, Nagwa M.

doi:10.18576/jsap/030105

Cited by 7 publications

(7 citation statements)

References 18 publications

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“…e type-II censoring can be considered a common type of censored scheme. Many authors have studied the statistical inference for different probability distributions using progressive type-II censoring, including Balakrishnan and Sandhu [1,2], Cohen [3], Mann [4], Ng [5], Balakrishnan et al [6], Gibbons and Vance [7], Yuen and Tse [8], Ng et al [9], Balakrishnan [10], Soliman [11,12], Madi and Raqab [13], Mahmoud et al [14], Mahmoud et al [15], Soliman et al [16], El-Sagheer [17][18][19], Mahmoud et al [20], El-Sagheer and Hasaballah [21], El-Sagheer et al [22], and Soliman et al [23]. Recently, Zhang and Gui [24] studied the statistical inference for the lifetime performance index of Pareto distribution based on progressive type-II censored sample.…”

Section: Introductionmentioning

confidence: 99%

Inferences for Generalized Pareto Distribution Based on Progressive First‐Failure Censoring Scheme

2021

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In this article, we consider estimation of the parameters of a generalized Pareto distribution and some lifetime indices such as those relating to reliability and hazard rate functions when the failure data are progressive first-failure censored. Both classical and Bayesian techniques are obtained. In the Bayesian framework, the point estimations of unknown parameters under both symmetric and asymmetric loss functions are discussed, after having been estimated using the conjugate gamma and discrete priors for the shape and scale parameters, respectively. In addition, both exact and approximate confidence intervals as well as the exact confidence region for the estimators are constructed. A practical example using a simulated data set is analyzed. Finally, the performance of Bayes estimates is compared with that of maximum likelihood estimates through a Monte Carlo simulation study.

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Section: Introductionmentioning

confidence: 99%

Inferences for Generalized Pareto Distribution Based on Progressive First‐Failure Censoring Scheme

2021

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“…Many authors have derived several recurrence relations for single and product moments of progressively Type-II right censored order statistics for various distributions. For example, see Balakrishnan and Aggarwala (2012), ; Balakrishnan et al (2001), , 2013, Mahmoud et al (2014), Malik and Kumar (2017), Singh and Khan (2019), Dey et al (2019), Kumar et al (2019) and Pushkarna et al (2020). The moments of usual order statistics have been recursively derived, for example, see Balakrishnan (1985), Balakrishnan et al (2015aBalakrishnan et al ( , 2015b, Akhter et al (2020) and Liu and Balakrishnan (2020), among others.…”

Section: Introductionmentioning

confidence: 99%

Moments of progressively type-II censored order statistics from the complementary exponential geometric distribution and associated inference

Alzahrani

AL-Zaydi

2021

Int J Syst Assur Eng Manag

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In this article, we establish some recurrence relations for both single and product moments of progressively Type-II right censored order statistics from the complementary exponential-geometric distribution. For a particular case, these relations are reduced to the corresponding results for the usual order statistics due to Balakrishnan et al. (J Stat Comput Simul 85(11): 2187-2201, 2015. Then we use these moments to obtain the best linear unbiased estimators of the scale and location-scale parameters of the complementary exponentialgeometric distribution based on progressively Type-II right censored samples. Further, we discuss the best linear unbiased predictors of future failure times. Finally, an example is presented to show the application of our results.

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“…Several authors obtained the recurrence relation for progressively type-II right censored order statistics for different distributions such as Cohin (1963), Mann [ (1971, Thomas and Wilson (1972), Arnold (1992), Balakrishnan et al (2012), Nikulin and Haghighi (2006), Haghighi (2011), Joshi (1978), Balakrishnan and Malik (1986), Arnold et al (1992), Viveros and Balakrishnan (1994), Balakrishnan and Sandhu (1995), Aggarwala and Balakrishnan (1996), Balakrishnan and Aggarwala (1998), Balakrishnan andSultan (1998), Abd El-Baset andMohammed (2003), David and Nagaraja (2003), Fernandez (2004), Balakrishnan et al (2004), Sultan et al (2006), Mahmoud et al (2006), Balakrishnan (2007), Bal-akrishnan et al (2011), Balakrishnan andSaleh (2013). The moments of order statistics have been recursively derived, see Salah et al (2008), Kumar and Sanku (2017) and , for a complete sample.…”

Section: Introductionmentioning

confidence: 99%

Relations for Moments of Progressively Type-II Right Censored Order Statistics From Erlang-Truncated Exponential Distribution

Malik

Kumar

2017

Statistics in Transition New Series

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In this paper, we establish some new recurrence relations for the single and product moments of progressively Type-II right censored order statistics from the Erlangtruncated exponential distribution. These relations generalize those established by Aggarwala and Balakrishnan (1996) for standard exponential distribution. These recurrence relations enable computation of mean, variances and covariances of all progressively Type-II right censored order statistics for all sample sizes in a simple and efficient manner. Further an algorithm is discussed which enable us to compute all the means, variances and covariances of Erlang-truncated exponential progressive Type-II right censored order statistics for all sample sizes n and all censoring schemes (R 1 , R 2 ,..., R m ), m < n. By using these relations, we tabulate the means and variances of progressively Type-II right censored order statistics of the Erlangtruncated exponential distribution.

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Progressively Censored Data from The Weibull Gamma Distribution Moments and Estimation

Cited by 7 publications

References 18 publications

Inferences for Generalized Pareto Distribution Based on Progressive First‐Failure Censoring Scheme

Inferences for Generalized Pareto Distribution Based on Progressive First‐Failure Censoring Scheme

Moments of progressively type-II censored order statistics from the complementary exponential geometric distribution and associated inference

Relations for Moments of Progressively Type-II Right Censored Order Statistics From Erlang-Truncated Exponential Distribution

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