Publisher: U of the Punjab   (Total: 5 journals)   [Sort by number of followers]

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Intl. J. of Business Reflections     Open Access   (Followers: 2)
Mycopath     Open Access  
Pakistan J. of Information Management & Libraries     Open Access   (SJR: 0.141, CiteScore: 0)
Pakistan J. of Statistics and Operation Research     Open Access   (Followers: 1, SJR: 0.383, CiteScore: 1)
Punjab University J. of Mathematics     Open Access   (Followers: 1)
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Pakistan Journal of Statistics and Operation Research
Journal Prestige (SJR): 0.383
Citation Impact (citeScore): 1
Number of Followers: 1  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1816-2711 - ISSN (Online) 2220-5810
Published by U of the Punjab Homepage  [5 journals]
  • Paradox in The d-Dimensional Fixed Charge Transportation Problem and
           Algorithm for Finding The Paradox

    • Authors: Bib Paruhum Silalahi, Eko Sulistyono, Fahren Bukhari
      Pages: 329 - 336
      Abstract: The d-dimensional fixed charge transportation problem is a generalization of fixed charge transportation. This problem has d-type of constraints so that can be applied to more complex problem. In transportation problem, sometimes there is a cases when increase the product in shipping, the number of costs incurred is less than before the increase of product. This problem is called the transportation paradox. In this research, it will be explained about the model of d-dimensional fixed charge transportation problem and sufficient condition for the occurrence of the paradox. Furthermore an algorithm is given in finding the paradox in the d-dimensional fixed charge transportation problem with example to support the theory presented.
      PubDate: 2022-06-01
      DOI: 10.18187/pjsor.v18i2.2807
       
  • Huber M-estimator for Cumulative Odds Model with Application to the
           Measurement of Students' Final Exam Grades

    • Authors: Faiz Bin Zulkifli, Zulkifley Bin Mohmed, Nor Afzalina Binti Azmee
      Pages: 337 - 347
      Abstract: The Huber M-estimator is proposed in this study as a robust method for estimating the parameters of the cumulative odds model, which includes a logistic link function and polytomous explanatory variables. With the help of an intensive Monte Carlo simulation study carried out using the statistical software R, this study evaluates the performance of the maximum likelihood estimator (MLE) and the robust technique developed. Bias, RMSE, and the Lipsitz Statistic are used to measure comparisons. When conducting the simulation study, different sample sizes, contamination proportions, and error standard deviations are considered. Preliminary findings indicate that the M-estimator with Huber weight estimates produces the best results for parameter estimation and overall model fitting compared to the MLE. As an illustration, the procedure is applied to real-world data of students' final exam grades as measured by two different estimators.
      PubDate: 2022-06-01
      DOI: 10.18187/pjsor.v18i2.2996
       
  • The Exponentiated Generalized Alpha Power Family of Distribution:
           Properties and Applications

    • Authors: ElSayed A. ElSherpieny, Ehab Mohamed Almetwally
      Pages: 349 - 367
      Abstract: In this paper, we introduce the exponentiated generalized alpha power family of distributions to extend the several other distributions. We used the new family to discuss the exponentiated generalized alpha power exponential (EGAPEx) distribution. Some statistical properties of the EGAPEx distribution are obtained. The model parameters are obtained by the maximum likelihood estimation (MLE), maximum product spacing (MPS) and Bayesian estimation methods. A Monte Carlo Simulation is performed to compare between different methods. We illustrate the performance of the proposed new family of distributions by means of two real data sets and the data sets show the new family of distributions is more appropriate as compared to the exponentiated generalized exponential, alpha power generalized exponential, alpha power exponential, generalized exponential and exponential distributions.
      PubDate: 2022-06-01
      DOI: 10.18187/pjsor.v18i2.3515
       
  • A New Transmuted Weibull Distribution: Properties and Application

    • Authors: Aliya Syed Malik, S.P. Ahmad
      Pages: 369 - 381
      Abstract: This paper proposes a new three parameter Weibull distribution obtained using a new Transmutation technique namely New Transmuted Weibull distribution. A comprehensive account of some of the mathematical properties of new model are derived. Entropy estimation and parameter estimation is also carried out using different methods. Finally, it will be shown that the analytical results are applicable to model real data.
      PubDate: 2022-06-01
      DOI: 10.18187/pjsor.v18i2.2728
       
  • The Effect Of International Aid On Per Capita Income: A Panel Data
           Analysis

    • Authors: Fatma Feyza GÜNDÜZ, Özlem AKAY
      Pages: 383 - 394
      Abstract: Poverty, a problem that has existed throughout the history of humanity and sought a solution, is a phenomenon that is struggled under the joint responsibility of world states, national and international organizations. As a result of the positive and economic developments after the World War II, with the implementation of social spending programs, a transition to a systematic structure has been achieved in the struggle against poverty. In this study, a panel data set covering the period 2004-2018 for 23 countries was constructed to examine the impact of international aid on per capita income. The study results show a positive relationship between the international aid, population, and human development index and per capita gross domestic product at the 5% significance level, a negative relationship between the unemployment rate and the Gini coefficient and per capita income at the 5% significance level. If the international aid increases by 1%, the per capita income increases by 0.08%, if the population increases by 1%, the per capita income increases by 1.45%,  if the value of human development increases by 1%, the per capita income increases by 1.60%. If the unemployment rate increases by 1%, per capita income decreases by 0.15%; if the Gini coefficient increases by 1%, the per capita income decreases by 0.63%.
      PubDate: 2022-06-01
      DOI: 10.18187/pjsor.v18i2.4042
       
  • The Infinite Divisibility of Compound Negative Binomial Distribution as
           the Sum of Laplace Distribution

    • Authors: Dodi Devianto, Stefi Amalia Fitri, Hazmira Yoza, Maiyastri Maiyastri
      Pages: 395 - 402
      Abstract: The infinite divisibility of compound negative binomial distribution especially as the sum of Laplace distribution has important roles in governing the mathematical model based on its characteristic function. In order to show the property of characteristic function of this compound negative binomial distribution, it is used Fourier-Stieltjes transform to have characteristic function and then governed the property of continuity and quadratic form by using analytical approaches. The infinite divisibility property is obtained by introducing a function satisfied the criteria to be a characteristic function such that its convolution has the characteristic function of compound negative binomial distribution. Then it is concluded that the characteristic function of compound negative binomial distribution as the sum of Laplace distribution satisfies the property of continuity, quadratic form and infinite divisibility.
      PubDate: 2022-06-01
      DOI: 10.18187/pjsor.v18i2.2767
       
  • New Exponential Ratio Estimator in Ranked Set Sampling

    • Authors: Rather Khalid, Eda Gizem KOÇYİĞİT, Ceren ÜNAL
      Pages: 403 - 409
      Abstract: In this study, we adapted the families of estimators from Ünal and Kadilar (2021)  using the exponential function for the population mean in case of non-response for simple random sampling for the estimation of the mean of the population with the RSS (ranked set sampling) method. The equations for the MSE and the bias of the adapted estimators are obtained for RSS and it in theory shows that the proposed estimator is additional efficient than the present RSS mean estimators in the literature. In addition, we support these theoretical results with real COVID-19 real data and conjointly the simulation studies with different distributions and parameters. As a result of the study, it was observed that the efficiency of the proposed estimator was better than the other estimators.
      PubDate: 2022-06-01
      DOI: 10.18187/pjsor.v18i2.3921
       
  • Decomposition Method with Application of Grey Model GM(1,1) for
           Forecasting Seasonal Time Series

    • Authors: Mujiati Dwi Kartikasari, Nur Hikmah
      Pages: 411 - 416
      Abstract: Forecasting is one of the activities needed by companies to determine the policies that need to be taken for the continuity of operations. There are many methods for forecasting, one of which is the grey model GM(1,1). The GM(1,1) is one of the successful forecasting methods applied to economics, finance, engineering, and others. However, according to several previous study, the GM(1,1) is not good enough to forecast data containing seasonal characteristics. Therefore, the aim of this study is to develop hybrid model so that the GM(1,1) is able to forecast seasonal time series. The hybrid model is constructed by combining decomposition method for seasonality adjustment and grey model GM(1,1) for forecasting seasonal time series. The results are compared to seasonal grey model SGM(1,1). Based on the evaluation using error criteria, it is found that the hybrid model is the best model.
      PubDate: 2022-06-01
      DOI: 10.18187/pjsor.v18i2.3533
       
  • Mathematical Modeling of Age-Specific Fertility Rates of Nepali Mothers

    • Authors: Arjun Kumar Gaire, Gyan Bahadur Thapa, Samir K. C.
      Pages: 417 - 426
      Abstract: In this paper, polynomial models have been formulated to describe the distribution pattern of age-specific fertility rates (ASFRs) and forward-cumulative ASFRs of Nepali mothers. The former follows the bi-quadratic polynomial and the latter follows the quadratic one. Velocity and elasticity equations of the fitted models have been formulated. The areas covered by the curves of the fitted models have been evaluated, and the area covered by the curve of ASFRs is equivalent to the total fertility rate (TFR). Furthermore, the mode of the fitted ASFRs has been estimated. To test the stability and validity of fitted models, cross validity prediction power, shrinkage of the model, F-test statistics and the coefficient of determination have been applied.
      PubDate: 2022-06-01
      DOI: 10.18187/pjsor.v18i2.3319
       
  • The Support Vector Regression Model: A new Improvement for some Data
           Reduction Methods with Application

    • Authors: Moustafa Salem, Mohamed G. Khalil
      Pages: 427 - 435
      Abstract: Support Vector Regression (SVR) formulates is an optimization problem to learn a regression function that maps from input predictor variables to output observed response values. The SVR is useful because it balances model complexity and prediction error, and it has good performance for handling high-dimensional data. In this paper, we use the SVR model to improve the principal component analysis and the factor analysis methods. Simulation experiments are performed to assessment the new method. Some useful applications to real data sets are presented for comparing the competitive SVR models. It is noted that with increasing sample size, the -SVR type under the principal component analysis is the best model. However, under the small sample sizes the SVR type under the factor analysis provided adequate results.
      PubDate: 2022-06-02
      DOI: 10.18187/pjsor.v18i2.4049
       
  • A New Flexible Probability Model: Theory, Estimation and Modeling Bimodal
           Left Skewed Data

    • Authors: Mohamed Aboraya, M. Masoom Ali, Haitham M. Yousof, Mohamed Ibrahim Mohamed
      Pages: 437 - 463
      Abstract: In this work, we introduced a new three-parameter Nadarajah-Haghighi model. We derived explicit expressions for some of it statistical properties. The Farlie Gumbel Morgenstern, modified Farlie Gumbel Morgenstern, Clayton, Renyi and Ali-Mikhail-Haq copulas are used for deriving some bivariate type extensions. We consider maximum likelihood, Cramér-von-Mises, ordinary least squares, whighted least squares, Anderson Darling, right tail Anderson Darling and left tail Anderson Darling estimation procedures to estimate the unknown model parameters. Simulation study for comparing estimation methods is performed. An application for comparing methods as also presented. The maximum likelihood estimation method is the best method. However, the other methods performed well. Another application for comparing the competitive models is investigated.
      PubDate: 2022-06-02
      DOI: 10.18187/pjsor.v18i2.3938
       
  • Spatial-temporal factors affecting monthly rainfall in some Central Asian
           countries assuming a Weibull regression model

    • Authors: Emerson Barili, Jorge Alberto Achcar, Ricardo Puziol de Oliveira
      Pages: 465 - 482
      Abstract: Climate change has been observed worldwide in the last years. Among the different effects of climate change, rain precipitation is one of the effects that most challenge the population of all countries in the world. The main goal of this study is to introduce a data analysis of monthly rainfall data related to five countries in Central Asia (Kazakhstan, Kyrgyzstan, Tadjikistan, Turkmenistan and Uzbekistan) for a long period of time to discover the behavior of rain precipitation in these countries in the last decades and possible link with climate change. Since climate data are positive real values, Weibull regression models are used in the data analysis in presence of some spatial factors  as latitude and longitude of the climate stations in each country, temporal factors (linear year effects), altitude of the climate station and categorical factors (countries).The obtained results show that some factors have different effects in the monthly rainfall of the assumed countries during the follow-up assumed period, possibly linked to the climate change observed in the last decades worldwide.
      PubDate: 2022-06-02
      DOI: 10.18187/pjsor.v18i2.3976
       
  • A New Generalized-X Family of Distributions: Applications,
           Characterization and a Mixture of Random Effect Models

    • Authors: Rasool Roozegar, Getachew Tekle, Gholamhossein Hamedani
      Pages: 483 - 504
      Abstract: The researchers in applied statistics are recently highly motivated to introduce new generalizations of distributions due to the limitations of the classical univariate distributions. In this study, we propose a new family called new generalized-X family of distributions. A special sub-model called new generalized-Weibull distribution is studied in detail. Some basic statistical properties are discussed in depth. The performance of the new proposed model is assessed graphically and numerically. It is compared with the five well-known competing models. The proposed model is the best in its performance based on the model adequacy and discrimination techniques. The analysis is done for the real data and the maximum likelihood estimation technique is used for the estimation of the model parameters. Furthermore, a simulation study is conducted to evaluate the performance of the maximum likelihood estimators. Additionally, we discuss a mixture of random effect models which are capable of dealing with the overdispersion and correlation in the data. The models are compared for their best fit of the data with these important features. The graphical and model comparison methods implied a good improvement in the combined model.
      PubDate: 2022-06-03
      DOI: 10.18187/pjsor.v18i2.4043
       
 
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