Journal of Statistical Theory and Applications

Volume 18, Issue 3, September 2019
Research Article

1. Gaussian Copula–based Regression Models for the Analysis of Mixed Outcomes: An Application on Household's Utilization of Health Services Data

Z. Rezaei Ghahroodi, R. Aliakbari Saba, T. Baghfalaki
Pages: 182 - 197
In analyzing most correlated outcomes, the popular multivariate Gaussian distribution is very restrictive and therefore dependence modeling using copulas is nowadays very common to take into account the association among mixed outcomes. In this paper, we use Gaussian copula to construct a joint distribution...
Research Article

2. Bivariate and Multivariate Weighted Kumaraswamy Distributions: Theory and Applications

Indranil Ghosh
Pages: 198 - 211
Weighted distributions (univariate and bivariate) have received widespread attention over the last two decades because of their flexibility for analyzing skewed data. In this paper, we derive the bivariate and multivariate weighted Kumaraswamy distributions via the construction method as discussed in...
Research Article

3. Simultaneous Optimization of Multiple Responses That Involve Correlated Continuous and Ordinal Responses According to the Gaussian Copula Models

Fatemeh Jiryaie, Ahmad Khodadadi
Pages: 212 - 221
This study investigates the simultaneous optimization of multiple correlated responses that involve mixed ordinal and continuous responses. The proposed approach is applicable for responses that have either an all ordinal categorical form are continuous but have different marginal distributions, or when...
Research Article

4. Bounded Risk Estimation of the Gamma Scale Parameter in a Purely Sequential Sampling Procedure

Eisa Mahmoudi, Ghahraman Roughani, Ashkan Khalifeh
Pages: 222 - 235
We consider the purely sequential procedure for estimating the scale parameter of a gamma distribution with known shape parameter, when the risk function is bounded by the known preassigned number. In this paper, we provide asymptotic formulas for the expectation of the total sample size. Also, we propose...
Research Article

5. E-Bayesian Estimation for the Exponential Model Based on Record Statistics

Hassan M. Okasha
Pages: 236 - 243
This paper is concerned with using the E-Bayesian method for computing estimates for the parameter and reliability function of the Exponential distribution based on a set of upper record statistics values. The estimates are derived based on a conjugate prior for the scale parameter and squared error...
Research Article

6. A Multivariate Skew-Normal Mean-Variance Mixture Distribution and Its Application to Environmental Data with Outlying Observations

M. Tamandi, N. Balakrishnan, A. Jamalizadeh, M. Amiri
Pages: 244 - 258
The presence of outliers, skewness, kurtosis, and dependency are well-known challenges while fitting distributions to many data sets. Developing multivariate distributions that can properly accomodate all these aspects has been the aim of several researchers. In this regard, we introduce here a new multivariate...
Research Article

7. On a Generalized Burr Life-Testing Model: Characterization, Reliability, Simulation, and Akaike Information Criterion

M. Ahsanullah, M. Shakil, B. M. Golam Kibria, M. Elgarhy
Pages: 259 - 269
For a continuous random variable X, M. Shakil, B.M.G. Kibria, J. Stat. Theory Appl. 9 (2010), 255–282, introduced a generalized Burr increasing, decreasing, and upside-down bathtub failure rate life-testing model. In this paper, we provide some characterizations of this life-testing model by truncated...
Research Article

8. On the Influence Function for the Theil-Like Class of Inequality Measures

Tchilabalo Abozou Kpanzou, Diam Ba, Pape Djiby Mergane, Gane Samb LO
Pages: 270 - 277
On one hand, a large class of inequality measures, which includes the generalized entropy, the Atkinson, the Gini, etc., for example, has been introduced in P.D. Mergane, G.S. Lo, Appl. Math. 4 (2013), 986–1000. On the other hand, the influence function (IF) of statistics is an important tool in the...
Research Article

9. The Odd Log-Logistic Geometric Family with Applications in Regression Models with Varying Dispersion

Maria do Carmo S. Lima, Fábio Prataviera, Edwin M. M. Ortega, Gauss M. Cordeiro
Pages: 278 - 294
We obtain some mathematical properties of a new generator of continuous distributions with two additional shape parameters called the odd log-logistic geometric family. We present some special models and investigate the asymptotes and shapes. The family density function can be expressed as a linear combination...
Research Article

10. Discriminating Between Exponential and Lindley Distributions

V. S. Vaidyanathan, A Sharon Varghese
Pages: 295 - 302
In literature, Lindley distribution is considered as an alternate to the exponential distribution. In the present work, a methodology is developed to discriminate between exponential and Lindley distributions based on the ratio of the maximum likelihoods. Asymptotic distribution of the test statistic...
Research Article

11. Characterization of Exponential Distribution Through Normalized Spacing of Generalized Order Statistics

M. J. S. Khan, S. Iqrar, M. Faizan
Pages: 303 - 308
In this paper, exponential distribution is characterized by normalized spacing of generalized order statistics (gos) using Meijer's G-function. While the necessary part of the theorem was given by U. Kamps, E. Cramer, Statistics. 35 (2001), 269–280, we have given an easy proof of sufficient part...
Research Article

12. Concomitants of Order Statistics and Record Values from Generalization of FGM Bivariate-Generalized Exponential Distribution

H. M. Barakat, E. M. Nigm, M. A. Alawady, I. A. Husseiny
Pages: 309 - 322
We introduce the generalized Farlie–Gumbel–Morgenstern (FGM) type bivariate-generalized exponential distribution. Some distributional properties of concomitants of order statistics as well as record values for this family are studied. Recurrence relations between the moments of concomitants are obtained,...
Research Article

13. On the Asymptotic Behavior in Random Fields: The Central Limit Theorem

Mohammad Mehdi Saber, Zohreh Shishebor, Behnam Amiri
Pages: 323 - 328
The aim of this paper is to provide an applicable version of Central Limit Theorem for strictly stationary m-dependent random fields on a lattice. The type of sampling is considered increasing domain sampling.