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Journal Cover International Journal of Advanced Statistics and Probability
  [3 followers]  Follow
  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
      DOI: 10.14419/ijasp.v5i1.6931
      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
      DOI: 10.14419/ijasp.v5i1.7410
      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
      DOI: 10.14419/ijasp.v5i1.7221
      Issue No: Vol. 5, No. 1 (2017)
  • Precision of full polynomial response surface designs on models with
           missing coefficients

    • Authors: Mary Iwundu, ENYINNA Jaja
      Pages: 32 - 36
      Abstract: The precision of using full polynomial response surface designs on models with missing coefficients (reduced models) is studied using efficiency measures. The loss in D- and G-efficiency of constructed first-order exact designs is minimized for the model with missing interaction coefficient. However, higher losses in D- and G-efficiency are recorded when constructed second-order exact designs are used on the model with missing interaction coefficient with few exceptions showing preferences for using the designs on the reduced model. Lower condition numbers are observed for the designs under the first-order reduced models thus indicating that the N-point exact designs are closer to being orthogonal for the reduced model than for the full model. Perfect orthoganality is achieved at design sizes 4 and 8. In fact, N-point exact designs of multiples of N=4 show perfect orthoganality when defined either for the full or reduced first-order models. In comparison to a design with perfect orthoganality, the second-order designs are far from being orthogonal.
      PubDate: 2017-05-03
      DOI: 10.14419/ijasp.v5i1.7491
      Issue No: Vol. 5, No. 1 (2017)
  • Analysis of semi-parametric single-index models by using MAVE-method based
           on some kernel functions

    • Authors: Fayyadh Ali, Tareq Salih
      Pages: 37 - 43
      Abstract: In this paper, we used many forms of kernel functions with minimum average variance estimation (MAVE) method [Xia2002] we called the proposed methods (MAVE-Biweight), (MAVE-Epanechnikov ) and .(MAVE-Gaussian ) for estimation the parameters and the link function of the single – index model (SIM) comparing with other methods of estimation . to evaluate the performing of the various methods s simulation and a real data have been used, conclusions showed that the (MAVE- Gaussian) method in this paper gave better results compared with other methods depending on the mean squared error (MSE) and mean Absolute error (MAE) criterion for comparison.
      PubDate: 2017-05-11
      DOI: 10.14419/ijasp.v5i1.7258
      Issue No: Vol. 5, No. 1 (2017)
  • A bivariate Pareto type I models

    • Authors: Mervat Abd Elaal, Hind Alzahrani
      Pages: 44 - 51
      Abstract: In this paper two new bivariate Pareto Type I distributions are introduced. The first distribution is based on copula, and the second distribution is based on mixture of and copula. Maximum likelihood and Bayesian estimations are used to estimate the parameters of the proposed distribution. A Monte Carlo Simulation study is carried out to study the behavior of the proposed distributions. A real data set is analyzed to illustrate the performance and flexibility of the proposed distributions.
      PubDate: 2017-05-16
      DOI: 10.14419/ijasp.v5i1.7638
      Issue No: Vol. 5, No. 1 (2017)
  • Characterization for Gompertz distribution based on general progressively
           type-II right censored order statistics

    • Authors: M. M. Mohie El-Din, A. Sadek, Marwa M. Mohie El-Din, A. M. Sharawy
      Pages: 52 - 56
      Abstract: In this article, we establish recurrence relations for single and product moments based on general progressively Type-II right censored order statistics (GPTIICOS). Characterization for Gompertz distribution (GD) using relation between probability density function and distribution function is obtained. Moreover recurrence relations of single and product moments based on GPTIICOS are also used to characterize the distribution. Further, the results are specialized to the progressively Type-II right censored order statistics (PTIICOS).
      PubDate: 2017-05-16
      DOI: 10.14419/ijasp.v5i1.7524
      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
      DOI: 10.14419/ijasp.v5i1.5713
      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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