Pakistan Journal of Statistics and Operation Research
http://pjsor.com/index.php/pjsor
Pakistan Journal of Statistics and Operation Researchen-US<p><strong>Authors who publish with this journal agree to the following terms:</strong></p><ul><li>Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a <a href="http://creativecommons.org/licenses/by/3.0/" target="_new">Creative Commons Attribution License</a> that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.</li></ul><div> </div><ul><li>Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.</li></ul><div> </div><ul><li>Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See <a href="http://opcit.eprints.org/oacitation-biblio.html" target="_new">The Effect of Open Access</a>).</li></ul><p><span><br /></span></p>editor@pjsor.com (Editor PJSOR)assoc.editor@pjsor.com (Support Team)Sat, 22 Jun 2019 10:59:14 +0500OJS 2.4.5.0http://blogs.law.harvard.edu/tech/rss60A New Extension of Lindley Geometric Distribution and its Applications
http://pjsor.com/index.php/pjsor/article/view/2328
<p>A new four-parameter distribution called the beta Lindley-geometric distribution is proposed. The hazard rate function of the new model can be constant, decreasing, increasing, upside down bathtub or bathtub failure rate shapes. Various structural properties including of the new distribution are derived. The estimation of the model parameters is performed by maximum likelihood method. The usefulness of the new distribution is illustrated using a real data set.</p>I. Elbatal, Mohamed G. Khalilhttp://pjsor.com/index.php/pjsor/article/view/2328Wed, 12 Jun 2019 22:13:31 +0500Scheduling of Student-development Activities via an Integration of Compromised-AHP and Transportation Model
http://pjsor.com/index.php/pjsor/article/view/2650
<p>One of the main challenges to schedule student-development activities in a university is to avoid time conflicts that may affect participation from the students. This can be achieved by having a proper planning and scheduling of student-development activities. In this paper, we demonstrate how Compromised-Analytic Hierarchy Process (C-AHP) and 0-1 Integer Programming (0-1 IP) models were utilized to schedule a set of student activities to be run by the UUM’s Student Body for the 2018/2019 academic year. The C-AHP was used to determine the activity-month preference values, while 0-1 IP models were constructed to schedule a set of student activities that can be executed successfully with high participation rates from the students. Two different 0-1 IP models, which can be viewed as transportation models: Model A and Model B were constructed. Model A was formulated without the month preference to conduct the activities, whereas Model B took consideration on the month preference. For Model A, the optimal result indicated that the activities scheduled were concentrated towards the earlier months of the academic year. On the other hand, the scheduling of activities provided by Model B was better-spread across the months of the academic year. The methods applied in this study will be useful to be implemented by organizations with many subunits in the management of planned activities in order to avoid time conflicts among activities, which in turn will minimize the chances of activity failure.</p>Engku Muhammad Nazri, Norazura Ahmad, Mohd Dino Khairri Shariffuddinhttp://pjsor.com/index.php/pjsor/article/view/2650Wed, 12 Jun 2019 22:14:19 +0500The New Odd Log-Logistic Generalised Half-Normal Distribution: Mathematical Properties and Simulations
http://pjsor.com/index.php/pjsor/article/view/2397
The new distributions are very useful in describing real data sets, because these distributions are more flexible to model real data that present a high degree of skewness and kurtosis. The choice of the best-suited statistical distribution for modeling data is very important.<br />In this paper, A new class of distributions called the {\it New odd log-logistic generalized half-normal} (NOLL-GHN) family with four parameters is introduced and studied. This model contains sub-models such as half-normal (HN), generalized half-normal (GHN )and odd log-logistic generalized half-normal (OLL-GHN) distributions.<br />some statistical properties such as moments and moment generating function have been calculated.<br />The Biases and MSE's of estimator methods such as maximum likelihood estimators , least squares estimators, weighted least squares estimators,<br />Cramer-von-Mises estimators, Anderson-Darling estimators and right tailed Anderson-Darling estimators are calculated.<br />The fitness capability of this model has been investigated by fitting this model and others based on real data sets. The maximum likelihood estimators are assessed with simulated real data from proposed model. We present the simulation in order to test validity of maximum likelihood estimators.Mahmoud afshari Afshari, Mosa Abdi, Hamid Karamikabir, Mahdiye Mozafari, Morad Alizadehhttp://pjsor.com/index.php/pjsor/article/view/2397Wed, 12 Jun 2019 22:14:55 +0500Bayesian Estimation of Latent Class Model for Survey Data Subject to Item Nonresponse
http://pjsor.com/index.php/pjsor/article/view/2612
<p>Latent variable models are widely used in social sciences for measuring constructs (latent variables) such as ability, attitude, behavior, and wellbeing. Those unobserved constructs are measured through a number of observed items (variables). The observed variables are often subject to item nonresponse, that may be nonignorable. Incorporating a missingness mechanism within the model used to analyze data with nonresponse is crucial to obtain valid estimates for parameters, especially when the missingness is nonignorable.</p><p>In this paper, we propose a latent class model (LCM) where a categorical latent variable is used to capture a latent phenomenon, and another categorical latent variable is used to summarize response propensity. The proposed model incorporates a missingness mechanism. Bayesian estimation using Markov Chain Monte Carlo (MCMC) methods are used for fitting this LCM. Real data with binary items from the 2014 Egyptian Demographic and Health Survey (EDHS14) are used. Different levels of missingness are artificially created in order to study results of the model under low, moderate and high levels of missingness.</p>Samah Zakaria, Mai Sherif Hafez, Ahmed Mahmoud Gadhttp://pjsor.com/index.php/pjsor/article/view/2612Wed, 12 Jun 2019 22:15:31 +0500On zeroes in sign and signed rank tests
http://pjsor.com/index.php/pjsor/article/view/2508
<p>When zeroes (or ties within pairs) occur in data being analyzed with a sign test or a signed rank test, nonparametric methods textbooks and software consistently recommend that the zeroes be deleted and the data analyzed as though zeroes did not exist. This advice is not consistent with the objectives of the majority of applications. In most settings a better approach would be to view the tests as testing hypotheses about a population median. There are relatively simple p-values available that are consistent with this viewpoint of the tests. These methods produce tests with good properties for testing a different (often more appropriate) set of hypotheses than those addressed by tests that delete the zeroes.</p>Rajarshi Dey, Justin Manjourides, Ronald H Randleshttp://pjsor.com/index.php/pjsor/article/view/2508Wed, 12 Jun 2019 22:16:03 +0500A Class of Ratio-Type Estimator Using Two Auxiliary Variables for Estimating The Population Mean With Some Known Population Parameters
http://pjsor.com/index.php/pjsor/article/view/2558
In this paper, we have suggested a class of ratio type estimators with a linear combination using two auxiliary variables with some known population mean of the study variable. The bias and the mean square error of the proposed estimators are derived. We identified sub-members of the class of ratio type estimators. The condition for which the the proposed the proposed estimators perform better than the sample mean per unit, Olkin (1958) multivariate ratio, classical linear regression estimator, Singh(1965), Mohanty (1967) and Swain (2012) are derived. From the analysis, it is observed that the proposed estimators perform better than the sample mean per unit and other existing ratio type estimators considered in this study.Toluwalase Janet Akingbade, Fabian C. Okaforhttp://pjsor.com/index.php/pjsor/article/view/2558Wed, 12 Jun 2019 22:17:00 +0500Construction of stratification points under optimum allocation using dynamic programming
http://pjsor.com/index.php/pjsor/article/view/2635
<p>In the present investigation, some theory has been developed for optimum stratification, when two auxiliary variables treated as the basis of stratification with one study variable under study. The problem has been formulated as mathematical programming problem and then solved by dynamic programming. Empirical studied have been made to illustrate the proposed method with the comparisons of other existing methods.</p>Faizan Danishhttp://pjsor.com/index.php/pjsor/article/view/2635Wed, 12 Jun 2019 22:17:31 +0500Posterior Predictive of Bayesian Vector Autoregressive (BVAR) and Adjusting Transformation on the Spatio Temporal Disaggregation Method: Predict Hourly rainfall data at the outsampled Locations
http://pjsor.com/index.php/pjsor/article/view/2651
This research is a development from previous research that has studied the method of spatio temporal disaggregation with State space and adjusting procedures for predicting hourly rainfall based on daily rainfall (Astutik et al, 2013). However, this study is limited to predicting hourly rainfall in some sampled locations in the future. Astutik et al (2017, 2018) have modeled hourly and daily rainfall using posterior predictive bayesian VAR at the Sampean watershed of Bondowoso. This study aims to predict hourly rainfall data based on daily rainfall data in the future at the outsampled locations using posterior predictive bayesian VAR and adjusting procedures in the method of spatio temporal disaggregation.Suci Astutik, Umu Sa’adah, Supriatna Adhisuwignjo, Rauzan Sumarahttp://pjsor.com/index.php/pjsor/article/view/2651Wed, 12 Jun 2019 22:18:12 +0500On Burr III-Pareto Distribution: Development, Properties, Characterizations and Applications
http://pjsor.com/index.php/pjsor/article/view/2938
<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA; mso-no-proof: yes;">In this paper, a new four parameter lifetime model with increasing, decreasing, increasing-decreasing, decreasing-increasing-decreasing, modified bathtub, bathtub and inverted bathtub hazard rate function called Burr III-Pareto (BIII-Pareto) is developed on the basis of the T-X family technique. The BIII-Pareto density function is arc, J-shape, reverse J-shape, positively, negatively skewed and symmetrical. Some structural and mathematical properties including moments, moments of order statistics, inequality measures and reliability measures are theoretically established. The BIII-Pareto distribution is characterized via different techniques. Parameters of the BIII-Pareto distribution are estimated using maximum likelihood method. The simulation study for performance of the maximum likelihood estimates (MLEs) of parameters for the BIII-Pareto distribution is carried out. The potentiality of the BIII-Pareto distribution is demonstrated by its application to real data sets. Goodness of fit of this distribution through different methods is studied. The BIII-Pareto distribution is empirically better for lifetime applications</span>Fiaz Ahmad Bhatti, G. G. Hamedani, Mustafa Ç. Korkmaz, Munir Ahmadhttp://pjsor.com/index.php/pjsor/article/view/2938Gibbs Sampling for Bayesian Prediction of SARMA Processes
http://pjsor.com/index.php/pjsor/article/view/2174
<p>In this article we present a Bayesian prediction of multiplicative seasonal autoregressive moving average (SARMA) processes using the Gibbs sampling algorithm. First, we estimate the unobserved errors using the nonlinear least squares (NLS) method to approximate the likelihood function. Second, we employ conjugate priors on the model parameters and initial values and assume the model errors are normally distributed to derive the conditional posterior and predictive distributions. In particular, we show that the conditional posterior distribution of the model parameters and the variance are multivariate normal and inverse gamma respectively, and the conditional predictive distribution of the future observations is a multivariate normal. Finally, we use these closed-form conditional posterior and predictive distributions to apply the Gibbs sampling algorithm to approximate empirically the marginal posterior and predictive distributions, enabling us easily to carry out multiple-step ahead predictions. We evaluate our proposed Bayesian method using simulation study and real-world time series datasets.</p>Ayman Aminhttp://pjsor.com/index.php/pjsor/article/view/2174Wed, 12 Jun 2019 22:36:59 +0500Odd Lindley-Lomax Model: Statistical Properties and Applications
http://pjsor.com/index.php/pjsor/article/view/2939
<p> </p><p><span style="font-family: Times New Roman;">In this work, we focus on some new theoretical and computational aspects of the Odd Lindley-Lomax model. The maximum likelihood estimation method is used to estimate the model parameters. We show empirically the importance and flexibility of the new model in modeling two types of aircraft windshield lifetime data. This model is much better than exponentiated Lomax, gamma Lomax, beta Lomax and Lomax models so the Odd Lindley-Lomax lifetime model is a good alternative to these models in modeling aircraft windshield data. A Monte Carlo simulation study is used to assess the performance of the maximum likelihood estimators.</span></p><p> </p>M. Masoom Ali, Mustafa Ç. Korkmaz, Haitham M. Yousof, Nadeem Shafique Butthttp://pjsor.com/index.php/pjsor/article/view/2939Bayesian inference on reliability in a multicomponent stress-strength bathtub-shaped model based on record values
http://pjsor.com/index.php/pjsor/article/view/2398
<p>In the literature, there are a well-developed estimation techniques for the reliability assessment in multicomponent stress-strength models when the information about all the experimental units are available. However, in real applications, only observations that exceed (or fall below) the current value may be recorded. In this paper, assuming that the components of the system follow bathtub-shaped distribution, we investigate Bayesian estimation of the reliability of a multicomponent stress-strength system when the available data are reported in terms of record values. Considering squared error, linex and entropy loss functions, various Bayes estimates of the reliability are derived. Because there are not closed forms for the Bayes estimates, we will use Lindley’s method to calculate the approximate Bayes estimates. Further, for comparison purposes, the maximum likelihood estimate of the reliability parameter is obtained. Finally, simulation studies are conducted in order to evaluate the performances of the proposed procedures and analysis of real data sets is provided.</p>Abbas Pak, Nayereh Bagheri Khoolenjani, Manoj Kumar Rastogihttp://pjsor.com/index.php/pjsor/article/view/2398Sat, 22 Jun 2019 10:44:24 +0500Modified Ratio Estimators of Population Mean Based on Ranked Set Sampling
http://pjsor.com/index.php/pjsor/article/view/2566
<p>In this paper, we propose modified ratio estimators using some known values of coefficient of variation, coefficient of skewness and coefficient of kurtosis of auxiliary variable under ranked set sampling (RSS). The mean square error (MSE) of the proposed ratio estimators under ranked set sampling is derived and compared with some existing ratio estimators under RSS. Through this comparison, we prove theoretically that MSC of proposed estimators is less than some existing ratio estimators in RSS under some conditions. The MSE of proposed estimators along with some existing estimator are also calculated numerically. We observe from numerical results that the suggested ratio estimators are more efficient than some existing ratio estimators under RSS.</p>Zahid Khan, Muhammad Ismailhttp://pjsor.com/index.php/pjsor/article/view/2566Sat, 22 Jun 2019 10:46:07 +0500Statistical modelling of the EUR/DZD returns with infinite variance distribution
http://pjsor.com/index.php/pjsor/article/view/2654
<p>Extreme values can cause considerable damage in several sectors and especially<br />in finance. In this article, we are interested in estimating some risk measures<br />for the series of the EURO exchange rate against the DZD (Algerian dinar)<br />using the lévy-stable distribution.</p>Ouadjed Hakimhttp://pjsor.com/index.php/pjsor/article/view/2654Sat, 22 Jun 2019 10:46:59 +0500A New Extension of the Lomax Distribution with Properties and Applications to Failure Times Data
http://pjsor.com/index.php/pjsor/article/view/2657
<span class="fontstyle0">A new lifetime model is introduced and studied. The major justi…cation for the practicality of the new model is based on the wider use of the Lomax model. We are also motivated to introduce the new model since the density of the new distribution exhibits various important shapes such as the unimodal, right skewed and left skewed. The new model can be viewed as a mixture of the exponentiated Lomax distribution. It can also be considered as a suitable<br />model for testing the symmetric, left skewed, right skewed and unimodal data. The maximum likelihood estimation method is used to estimate the model parameters. We prove empirically the importance and ‡exibility of the new model in modeling two types of aircraft windshield lifetime data sets. The proposed lifetime model is much better than gamma Lomax, beta Lomax, exponentiated Lomax and Lomax models so the exponentiated Lomax, model is a good alternative to these models in modeling aircraft windshield data.</span>Mohamed Abo Rayahttp://pjsor.com/index.php/pjsor/article/view/2657Sat, 22 Jun 2019 10:47:46 +0500Fuzzy Data envelopment Analysis with SBM using α-level Fuzzy Approach
http://pjsor.com/index.php/pjsor/article/view/2051
<p>The applications of fuzzy analysis in data-oriented techniques are the challenging aspect in the field of applied operational research. The use of fuzzy set theoretic measure is explored here in the context of data envelopment analysis (DEA) where we are utilizing the fuzzy α-level approach in the three types of efficiency models. Namely, BCC models, SBM model and supper efficiency model in DEA. It was observed from the result that the fuzzy SBM model has good discrimination power over fuzzy BCC. On the other side, both the models fuzzy BCC and fuzzy SBM are not able to make the genuine ranking which is acceptable for all. So this weakness is overcome with the help of fuzzy super SBM model and all three models are applied to illustrate the types of decisions and solutions that are achievable when the data are vague and prior information is in imprecise.</p><p> In this paper, we are considering that our inputs and outputs are not known with absolute precision in DEA and here, we using Fuzzy-DEA models based on an α-level fuzzy approach to assessing fuzzy data. </p>Qaiser Farooq Dar, Ahn Young Hyo, Gulbadian Farooq Dar, Shariq Ahmad Bhat, Arif Muhammad Tali, Yasir Hamid Bhathttp://pjsor.com/index.php/pjsor/article/view/2051Sat, 22 Jun 2019 10:49:53 +0500Type II General Exponential Class of Distributions
http://pjsor.com/index.php/pjsor/article/view/1699
In this paper, a new class of continuous distributions with two extra positive parameters is introduced and is called the Type II General Exponential (TIIGE) distribution. Some special models are presented. Asymptotics, explicit expressions for the ordinary and incomplete moments, moment residual life, reversed residual life, quantile and generating functions and stress-strengh reliability function are derived. Characterizations of this family are obtained based on truncated moments, hazard function, conditional expectation of certain functions of the random variable are obtained. The performance of the maximum likelihood estimators in terms of biases, mean squared errors and confidence interval length is examined by means of a simulation study. Two real data sets are used to illustrate the application of the proposed class.G. G. Hamedani, Mahdi Rasekhi, Sayed Najibi, Haitham M. Yousof, Morad Alizadehhttp://pjsor.com/index.php/pjsor/article/view/1699Sun, 23 Jun 2019 06:43:57 +0500