Open Access Original Research Article

Odoma Distribution and Its Application

C. C. Odom, M. A. Ijomah

Asian Journal of Probability and Statistics, Page 1-11
DOI: 10.9734/ajpas/2019/v4i130103

In this study, a new continuous one parameter lifetime distribution is proposed. Its mathematical properties such as moments, order statistics, entropy, survival function, hazard rate function and mean residual life function are derived. The new distribution is applied to real-life data from engineering and the method of maximum likelihood is used to estimate the parameter. The goodness-of-fit of the new distribution shows its better fit to the data than some competing distributions.

Open Access Original Research Article

Modified Laplace Distribution, Its Statistical Properties and Applications

F. I. Agu, C. E. Onwukwe

Asian Journal of Probability and Statistics, Page 1-14
DOI: 10.9734/ajpas/2019/v4i130104

Increasing the parameter of a distribution helps to capture the skewness and peakedness characteristic in the data sets. This allows a more realistic modeling of data arising from different real life situations. In this paper, we modified Laplace distribution using the exponentiation method. The study proved that the modified Laplace distribution (MLD) is a probability density function. Some of the basic statistical properties of the modified Laplace distribution are obtained. We applied the proposed modified Laplace distribution on two life datasets and simulated data. Parameters of the distributions were estimated using method of maximum likelihood estimation. The study compared the modified Laplace distribution with Laplace distribution and Generalized error distribution using Schwartz Criteria (SC) measure of fitness. The results obtained revealed that the modified Laplace distribution has a better fit than the Laplace and Generalized error distributions and can be used for more realistic modeling of data arising from different real life situations. The simulation results obtained shows that as the sample size increases, the Biasedness and Root Mean Square Error (RMSE) of the proposed modified Laplace distribution reduces.

Open Access Original Research Article

Bayesian Models for Zero Truncated Count Data

Olumide S. Adesina, Dawud A. Agunbiade, Pelumi E. Oguntunde, Tolulope F. Adesina

Asian Journal of Probability and Statistics, Page 1-12
DOI: 10.9734/ajpas/2019/v4i130105

It is important to fit count data with suitable model(s), models such as Poisson Regression, Quassi Poisson, Negative Binomial, to mention but a few have been adopted by researchers to fit zero truncated count data in the past. In recent times, dedicated models for fitting zero truncated count data have been developed, and they are considered sufficient. This study proposed Bayesian multi-level Poisson and Bayesian multi-level Geometric model, Bayesian Monte Carlo Markov Chain Generalized linear Mixed Models (MCMCglmms) of zero truncated Poisson and MCMCglmms Poisson regression model to fit health count data that is truncated at zero. Suitable model selection criteria were used to determine preferred models for fitting zero truncated data. Results obtained showed that Bayesian multi-level Poisson outperformed Bayesian multi-level Poisson Geometric model; also MCMCglmms of zero truncated Poisson outperformed MCMCglmms Poisson.

Open Access Original Research Article

Small Area Procedures for Estimating Income and Poverty in Egypt

Mai M. Kamal El Saied, Amal A. Talat, Mervat M. El Gohary

Asian Journal of Probability and Statistics, Page 1-17
DOI: 10.9734/ajpas/2019/v4i130106

In recent years, the demand for small area statistics has greatly increased worldwide. A recent application of small area estimation (SAE) techniques is in estimating local level poverty measures in Third World countries which is necessary to achieve the Millennium Development Goals. The aim of this research is to study SAE procedures for estimating the mean income and poverty indicators for the Egyptian provinces. For this goal the direct estimators of mean income and (FGT) poverty indicators for all the Egyptian provinces are presented. Also this study applies the empirical best/Bayes (EB) and the pseudo empirical best/Bayes (PEB) methods based on the unit level - nested error - model to estimate mean income and (FGT) poverty indicators for the Egyptian border provinces with (2012-2013) income, expenditure and consumption survey (IECS) data. The (MSEs) and coefficient of variations (C.Vs) are calculated for comparative purposes. Finally the conclusions are introduced. The results show that EB estimators for poverty incidence and poverty gap are smaller than PEB for all selected provinces. EB figures indicate that the largest poverty incidence and gap are for the selected municipality at the scope of the border south west of Egypt (New Valley). The PEB figures indicate that the largest poverty incidence and gap are for the selected municipality at the scope of the border north east of Egypt (North Sinai). As expected, estimated C.Vs for EB of poverty incidence and poverty gap estimators are noticeably larger than those of PEB estimators in all selected provinces.

Open Access Original Research Article

Determining the End Points of the Score Confidence Interval Using Computer Program

Rishi Raj Subedi, James Issos

Asian Journal of Probability and Statistics, Page 1-7
DOI: 10.9734/ajpas/2019/v4i130107

For interval estimation of a proportion the Score Interval is quite accurate. It has good reviews in the Statistics literature. But the problem is that it is not used enough. A reason is that many consider it is complicated. In this paper, we suggest a program and other things that we hope will make the Score Interval more suitable to use in the field of statistics.