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Journal Cover International Journal of Advanced Statistics and Probability
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  This is an Open Access Journal Open Access journal
   ISSN (Print) 2307-9045 - ISSN (Online) 2307-9045
   Published by Science Publishing Corporation Homepage  [12 journals]
  • Identification of correlation structure using rotated factor loadings

    • Authors: Iberedem Iwok, Nwikpe B. J
      Pages: 8 - 16
      Abstract: This work seeks to identify the correlation structure of variables in terms of few underlying but unobservable factors. The method was applied to age and five different tests results obtained from 200 patients in a hospital. Two factors were identified using the scree plot and the Kaiser criterion. The factor loadings obtained by the method of principal components gave an inadequate fit to the data. An algebraic approach was applied using orthogonal rotation, and the loadings were found to give a clear and interpretable pattern. Consequently, the variables: age, fasting blood sugar and diastolic blood pressure were found to cluster about the first factor F1 called Age-Cardiovascular factor. Similarly, the remaining variables malaria, typhoid and haemoglobin clustered about the second factor F2 and the given name was Hemo-typhomalaria factor. Diagnostic checks were carried out and the factor model generated by the rotated loadings was found to be adequate.
      PubDate: 2017-01-31
      Issue No: Vol. 5, No. 1 (2017)
  • Mathematical properties of the Kumaraswamy-Lindley distribution and its

    • Authors: Hamdy Salem, Abd-Elwahab Hagag
      Pages: 17 - 22
      Abstract: In this paper, a composite distribution of Kumaraswamy and Lindley distributions namely, Kumaraswamy-Lindley Kum-L distribution is introduced and studied. The Kum-L distribution generalizes sub-models for some widely known distributions. Some mathematical properties of the Kum-L such as hazard function, quantile function, moments, moment generating function and order statistics are obtained. Estimation of parameters for the Kum-L using maximum likelihood estimation and least square estimation techniques are provided. To illustrate the usefulness of the proposed distribution, simulation study and real data example are used.
      PubDate: 2017-03-11
      Issue No: Vol. 5, No. 1 (2017)
  • Estimation and application in log-Fréchet regression model using
           censored data

    • Authors: Hanan Alamoudi, Salwa‎ Mousa‎, Lamya Baharith
      Pages: 23 - 31
      Abstract: This article introduces a new location-scale regression model based on a log-Fréchet distribution. Maximum likelihood and Jackknife methods are used to estimate the new model parameters for censored data. Martingale and deviance residuals are obtained to check model assumptions, data validity, and detect outliers. Moreover, global influence is used to detect influential observations. Monte Carlo simulation study is provided to compare the performance of the maximum likelihood and jackknife estimators for different sample sizes and censoring percentages. The empirical distribution of the martingale and deviance residuals of the proposed model is examined. A real lifetime heart transplant data is analyzed under the log-Fréchet regression model to illustrate the satisfactory results of the proposed model.
      PubDate: 2017-03-18
      Issue No: Vol. 5, No. 1 (2017)
  • Multivariate statistical process control approach to monitor quality of
           chloroquine phosphate tablet (bp250mg) in Dana pharmaceutical company

    • Authors: Umar Abubakar Adamu, Gulumbe Shehu Usman, Dikko Hussaini Garba
      Pages: 1 - 7
      Abstract: Recently, much attention has been raised on effects of high increase in drugs counterfeiting and sub-standard quality which leads to many casualties in Nigeria. The Multivariate Statistical Process Control Charts approach was employed to examine such defects especially in assessing the official physico-chemical quality of chloroquine phosphate tablet (BP250mg) which claimed to contain the required quality properties. The Multivariate Exponentially Weighted Moving Average (MEWMA) Control Chart gives a powerful and reliable control chart than the widely used Hotelling’s T2˗Control Chart, which detects the smallest shift in the product process means and have minimum process variability. Also, the Matrix of scatter plots indicated the existence of relationship among the process variables and the Principal Component Analysis (PCA) minimized the rate of dimensionality of the process variability, which captured most of the variables outliers and retained the first Principal Components (PC) that explained over 99% variability of the product. To this end, the study results shows that the product quality characteristics (process variables) is under control (stable) and conform to international standard as specified by BP 2002.
      PubDate: 2016-12-13
      Issue No: Vol. 5, No. 1 (2016)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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Fax: +00 44 (0)131 4513327
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