Open Access Short Research Article

Modified Maximum Likelihood Estimation for Generalized Exponential Distribution

Alok Kumar Singh, Rohit Patawa, Abhinav Singh, Puneet Kumar Gupta

Asian Journal of Probability and Statistics, Page 48-59
DOI: 10.9734/ajpas/2021/v14i330332

For a Modified Maximum Likelihood Estimate of the parameters of generalized exponential distribution (GE), a hyperbolic approximation is used instead of linear approximation for a function which appears in the Maximum Likelihood equation. This estimate is shown to perform better, in accuracy and simplicity of calculation, than the one based on linear approximation for the same function. Numerical computation for random samples of different sizes from generalized exponential distribution (GE), using type II censoring is done and is shown to be better than that obtained by Lee et al. [1].

Open Access Original Research Article

Canonical Correlation of Multivariate Regression Analysis on Economic Factors in Nigeria

E. E. Bassey, U. P. Akra

Asian Journal of Probability and Statistics, Page 1-7
DOI: 10.9734/ajpas/2021/v14i330327

This research is on canonical correlation of multivariate regression analysis on economic factors in Nigeria. This study aim to analyze the effect of Nigerian macroeconomic factors and also to investigate the relationship between the factors for the period of 1985-2014. Four macroeconomic variables (economic factors) used in this research are Gross Domestic Product (GDP), Currency in Circulation (CIC), Foreign Trade and Inflation. Canonical correlation analysis under Multivariate regression was used for association between the variables. The result showed that there is a significant relationship between GDP and all the variables considered at (0.01) level of significant with the exception of inflation which showed negative and no significant relationship. However, the results also revealed that the economy of Nigeria is been affected by volume of economic factor returns.

Open Access Original Research Article

Spatial Modelling of Malaria Prevalence in Kenya

Morris Mwenda John, Elphas Luchemo, Ayubu Anapapa

Asian Journal of Probability and Statistics, Page 8-21
DOI: 10.9734/ajpas/2021/v14i330328

Malaria is one of the leading causes of deaths in Kenya. Malaria is a vector-borne disease caused by a parasite of the genus plasmodium. Complete eradication of malaria in the country has remained a problem. A lot of effort and resources has been put in the fight against malaria in developing countries which has led to underdevelopment and low human development index. Malaria burden affects the world’s poorest countries. About 90% of the malaria burden is reported in sub-Saharan Africa. The disease has led to high mortality cases in children and pregnant women. Despite the massive government eradication campaign, new and resurgent cases have been recorded. The specific objective was to determine the malaria risk factors and spatial distribution in Kenya. The 2015 malaria indicator survey data was used for the study. Demographic and social-economic factors were used as predictor variables. A generalized linear mixed model was used to determine the spatial variation and prevalence of malaria in Kenya. Demographic and social-economic factors were found to have significant impact on Prevalence of malaria in kenya. Most cases of malaria were reported in lake, western and coastal regions. The most prone areas were Kisumu, Homabay, Kakamega and Mombasa. There were less cases in central Kenya counties like Nyeri, Tharaka-Nithi with a significant number reported in arid and semi-arid regions of Northern-Kenya counties of Garissa, Mandera, Baringo. Rural population was more susceptible to malaria compared to those in urban areas. The odds of getting (verse not getting malaria) in places of residence increases by 1.32, which is estimated to .28, CIs 95% (1.01, 1.72), and a p-value .04. Malaria prevalence varied significantly from one region to another. The study established that Spatial autocorrelation exists among regions mostly due to weather patterns, geography, cultural practices and socio-economic factors.

Open Access Original Research Article

Robustness Test of the Two Stage K-L Estimator in Models with Multicollinear Regressors and Autocorrelated Error Term

Zubair Mohammed Anono, Adenomon Monday Osagie

Asian Journal of Probability and Statistics, Page 22-33
DOI: 10.9734/ajpas/2021/v14i330330

In a classical multiple linear regression analysis, multicollinearity and autocorrelation are two main basic assumption violation problems. When multicollinearity exists, biased estimation techniques such as Maximum Likelihood, Restricted Maximum Likelihood and most recent the K-L estimator by Kibria and Lukman [1] are preferable to Ordinary Least Square. On the other hand, when autocorrelation exist in the data, robust estimators like Cochran Orcutt and Prais-Winsten [2] estimators are preferred. To handle these two problems jointly, the study combines the K-L with the Prais-Winsten’s two-stage estimator producing the Two-Stage K-L estimator proposed by Zubair & Adenomon [3]. The Mean Square Error (MSE) and Root Mean Square Error (RMSE) criterion was used to compare the performance of the estimators. Application of the estimators to two (2) real life data set with multicollinearity and autocorrelation problems reveals that the Two Stage K-L estimator is generally the most efficient.

Open Access Original Research Article

Replenishment Model with Entropic Order Quantity for Deteriorating Items under Inflation

P. K. Tripathy, Anima Bag

Asian Journal of Probability and Statistics, Page 34-47
DOI: 10.9734/ajpas/2021/v14i330331

The purpose of the current paper is to determine an optimal order quantity so as to minimize the total cost of the inventory system of a business enterprise. The model is developed for deteriorating items with stock and selling price dependent demand under inflation without permitting shortage. Optimal solution is achieved by cost minimization strategy considering replenishment cost, purchase cost, holding cost and deterioration cost with a special approach to entropy cost for bulk size purchasing units. The effectiveness of the proposed model has been avowed through empirical investigation. Sensitivity analysis has been accomplished to deduce managerial insights. Findings suggest that an increased inflationary effect results in increment in the system total cost. The paper can be extended by allowing shortage. The model can be utilized in the business firms dealing with bulk purchasing units of electric equipments, semiconductor devices, photographic films and many more.