An EM algorithm for the estimation of parameters of bivariate generalized exponential distribution under random left censoring

Dewan, Isha; Nandi, Swagata

doi:10.1080/00949655.2012.668548

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…We analyze the data for the first two days, which are presented in Table (4). On Nasal drainage severity score data set [14], we fit the BDNH distribution, BDW distribution, and BDGE distribution and the results are listed in Table (5).…”

Section: Nasal Drainage Severity Scorementioning

confidence: 99%

“…To assess the fitness of the proposed and other related models for this data set and to evaluate the performance of the different estimation methods, we calculate the bias, RMSE, AIC, BIC and log-likelihood reported in Table (5). It is observed from the table that the proposed model is the best as compared to other models, as BDNH has the lowest AIC and BIC compared to BDW and BDGE distributions.…”

Section: Nasal Drainage Severity Scorementioning

confidence: 99%

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Bivariate discrete Nadarajah and Haghighi distribution: Properties and different methods of estimation

Ali

Shafqat

Shah

et al. 2019

Filomat

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The exponential distribution is commonly used to model different phenomena in statistics and reliability engineering. A new extension of exponential distribution known as the Nadarajah and Haghighi [An extension of the exponential distribution, Statistics: A Journal of Theoretical and Applied Statistics 45 (2011) 543-558.] distribution was introduced in the literature to accommodate the inflation of zero in the data. In practice, however, discrete data are easy to collect as compared to continuous data. Discrete bivariate distributions play important roles in modeling bivariate lifetime count data. Thus focusing on the utility of discrete data, this study presents a new bivariate discrete Nadarajah and Haghighi distribution. We discuss some basic properties of the proposed distribution and study seven different methods of estimation for the unknown parameters to assess the performance of the proposed bivariate discrete model. Two data sets are also analyzed to demonstrate how the proposed model may work in practice. Results show that the proposed model is very flexible and performs better than some of the existing models.

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Section: Nasal Drainage Severity Scorementioning

confidence: 99%

Section: Nasal Drainage Severity Scorementioning

confidence: 99%

Bivariate discrete Nadarajah and Haghighi distribution: Properties and different methods of estimation

Ali

Shafqat

Shah

et al. 2019

Filomat

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“…Kundu and Gupta [9] provided several properties and discussed inferential issues of the above mentioned model in details. For some recent work on the BGE distribution one is referred to Ashour et al [1], Dey and Kundu [4], Dewan and Nandi [3], Genc [5] and the references cited there in.…”

Section: The Bge Distributionmentioning

confidence: 99%

Bivariate discrete generalized exponential distribution

Nekoukhou

Kundu

2017

Statistics

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In this paper we develop a bivariate discrete generalized exponential distribution, whose marginals are discrete generalized exponential distribution as proposed by Nekoukhou, Alamatsaz and Bidram ("Discrete generalized exponential distribution of a second type", Statistics, 47, 876 -887, 2013). It is observed that the proposed bivariate distribution is a very flexible distribution and the bivariate geometric distribution can be obtained as a special case of this distribution. The proposed distribution can be seen as a natural discrete analogue of the bivariate generalized exponential distribution proposed by Kundu and Gupta ("Bivariate generalized exponential distribution", Journal of Multivariate Analysis, 100, 581 -593, 2009). We study different properties of this distribution and explore its dependence structures. We propose a new EM algorithm to compute the maximum likelihood estimators of the unknown parameters which can be implemented very efficiently, and discuss some inferential issues also. The analysis of one data set has been performed to show the effectiveness of the proposed model. Finally we propose some open problems and conclude the paper.

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Estimation of Parameters in a Bivariate Generalized Exponential Distribution Based on Type-II Censored Samples

Kim

Jang

2016

Communications in Statistics - Simulation and Computation

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An EM algorithm for the estimation of parameters of bivariate generalized exponential distribution under random left censoring

Cited by 3 publications

References 11 publications

Bivariate discrete Nadarajah and Haghighi distribution: Properties and different methods of estimation

Bivariate discrete Nadarajah and Haghighi distribution: Properties and different methods of estimation

Bivariate discrete generalized exponential distribution

Estimation of Parameters in a Bivariate Generalized Exponential Distribution Based on Type-II Censored Samples

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