Journal of Statistical Theory and Applications
Volume 19, Issue 4, December 2020
Research Article
1. A Modification of the Gompertz Distribution Based on the Class of Extended-Weibull Distributions
Mohammad Reza Kazemi, Ali Akbar Jafari, Saeid Tahmasebi
Pages: 472 - 480
This paper introduces a new four-parameter extension of the generalized Gompertz distributions. This distribution involves some well-known distributions such as extension of generalized exponential, generalized exponential, and generalized Gompertz distributions. In addition, it can have a decreasing,...
Research Article
2. Modified Maximum Likelihood Estimations of the Epsilon-Skew-Normal Family
Parichehr Jamshidi, Mohsen Maleki, Zahra Khodadadi
Pages: 481 - 486
In this work, maximum likelihood (ML) estimations of the epsilon-skew-normal (ESN) family are obtained using an EM-algorithm to modify the ordinary estimation already used and solve some of its problems within issues. This family can be used for analyzing the asymmetric and near-normal data, so the skewness...
Research Article
3. Transmuted Kumaraswamy Weibull Distribution with Covariates Regression Modelling to Analyze Reliability Data
Muhammad Shuaib Khan, Robert King, Irene Lena Hudson
Pages: 487 - 505
This paper investigates the potential usefulness of the transmuted Kumaraswamy Weibull distribution by using quadratic rank transmutation map technique for modelling reliability data. Some structural properties of the transmuted Kumaraswamy Weibull distribution are discussed. We propose a location-scale...
Research Article
4. Pranav Quasi Gamma Distribution: Properties and Applications
Sameer Ahmad Wani, Anwar Hassan, Shaista Shafi, Sumeera Shafi
Pages: 506 - 517
We have developed Pranav Quasi Gamma Distribution (PQGD) as a mixture of Pranav distribution (θ) and Quasi Gamma distribution (2,θ). We obtained various necessary statistical characteristics of PQGD. The flexibility of proposed model is clear from graph of hazard function. The reliability measures of...
Research Article
5. A Class of Beta Second Kind Mixture Distributions
Mian Arif Shams Adnan, Humayun Kiser
Pages: 518 - 525
A class of mixture distributions have been derived which we call beta second kind mixtures of distributions. Various integral representations of beta functions can be obtained using these mixture beta distributions. Estimation of unknown parameters along with some characteristics of these distributions...
Research Article
6. Measure of Departure from Point Symmetry and Decomposition of Measure for Square Contingency Tables
Kiyotaka Iki, Sadao Tomizawa
Pages: 526 - 533
For square contingency tables with ordered categories, Tomizawa, Biometrica J. 28 (1986), 387–393, considered the conditional point symmetry model. Kurakami et al., J. Stat. Adv. Theory Appl. 17 (2017), 33–42, considered the another point symmetry and the reverse global symmetry model. The present paper...
Research Article
7. An Unbiased Estimator of Finite Population Mean Using Auxiliary Information
B. Mahanty, G. Mishra
Pages: 534 - 539
In this paper, an unbiased estimator is constructed by using a linear combination of an estimator of study variable and mean per unit estimator of an auxiliary variable under simple random sampling without replacement scheme. The efficiency of the estimator under optimality compared with the mean per...
Research Article
8. Bayes Factors for Comparison of Two-Way ANOVA Models
R. Vijayaragunathan, M. R. Srinivasan
Pages: 540 - 546
In the traditional two-way analysis of variance (ANOVA) model, it is possible to identify the significance of both the main effects and their interaction based on the P values. However, it is not possible to determine how much data supports the model when these effects are incorporated into the model....
Research Article
9. Classical and Bayesian Inference for the Burr Type XII Distribution Under Generalized Progressive Type I Hybrid Censored Sample
Parya Parviz, Hanieh Panahi
Pages: 547 - 557
This paper describes the classical and Bayesian estimation for the parameters of the Burr Type XII distribution based on generalized progressive Type I hybrid censored sample. We first discuss the maximum likelihood estimators of unknown parameters using the expectation-maximization (EM) algorithm and...