Pakistan Journal of Statistics and Operation Research最新文献_第4页

A New Inverse Kumaraswamy Family of Distributions: Properties and Application 一个新的逆Kumaraswamy分布族：性质与应用

IF 1.5

Pakistan Journal of Statistics and Operation Research Pub Date : 2023-06-02 DOI: 10.18187/pjsor.v19i2.4295

A. M. Daghistani, Bander Al-Zahrani, M. Shahbaz

引用次数: 0

GOLD DISTRIBUTION Another Look on the Generalization of Lindely Distribution GOLD分布——对Lindely分布推广的再认识

IF 1.5

Pakistan Journal of Statistics and Operation Research Pub Date : 2023-06-02 DOI: 10.18187/pjsor.v19i2.3255

Mohammad Al-Talib, Amjad D. Al-Nasser, E. Ciavolino

引用次数: 1

The Ordinal Regression to Analyze Radical Intention of Muslim Indonesian Students through Personality Type and Tolerance Approach 从人格类型和容忍度分析印尼穆斯林学生激进倾向的有序回归

IF 1.5

Pakistan Journal of Statistics and Operation Research Pub Date : 2023-06-02 DOI: 10.18187/pjsor.v19i2.3932

A. Meiza

{"title":"The Ordinal Regression to Analyze Radical Intention of Muslim Indonesian Students through Personality Type and Tolerance Approach","authors":"A. Meiza","doi":"10.18187/pjsor.v19i2.3932","DOIUrl":"https://doi.org/10.18187/pjsor.v19i2.3932","url":null,"abstract":"This paper presents a result of research about the studentâ€™s radical intention related to their tolerance and personality type. This research was a collaboration between Statistics, Psychology, and Politics. The main research variable that is radical intention has a psychological construct that is theoretically built with a social approach and political point of view. As a big country, Indonesia has various pluralism i.e ethnic and religion, so that it requires a high tolerance attitude to live in a harmony. Students as the next generation and important elements in society are expected to avoid intolerance. The research subjects were 175 students from an Islamic university in Indonesia. The data were analyzed with Ordinal Regression which intention of radicalism (ordinal) as the dependent variable, personality type (nominal), and tolerance attitude level (ordinal) as independent variables. The majority of these students have good moral values so they can tolerate the difference. From the regression analysis, the type personality and tolerance attitude have a significant effect on radicalism intention.","PeriodicalId":19973,"journal":{"name":"Pakistan Journal of Statistics and Operation Research","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42189248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Generalization of Burr Type XII Distribution with Properties, Copula and Modeling Symmetric and Skewed Real Data Sets Burr型XII分布的性质、Copula及对称和斜交实数据集建模的推广

IF 1.5

Pakistan Journal of Statistics and Operation Research Pub Date : 2023-03-06 DOI: 10.18187/pjsor.v19i1.3377

Mohamed G. Khalil, Emadeldin I. A. Ali

引用次数: 1

Kumaraswamy Esscher Transformed Laplace Distribution: Properties, Application and Extensions Kumaraswamy Esscher变换拉普拉斯分布：性质、应用和扩展

IF 1.5

Pakistan Journal of Statistics and Operation Research Pub Date : 2023-03-06 DOI: 10.18187/pjsor.v19i1.3818

Dais George, Rimsha H.

引用次数: 0

The Marshall-Olkin Pranav distribution: Theory and applications Marshall-Olkin-Pranav分布：理论与应用

IF 1.5

Pakistan Journal of Statistics and Operation Research Pub Date : 2023-03-06 DOI: 10.18187/pjsor.v19i1.4058

Rehab Alsultan

引用次数: 0

Comparison of Infinite Capacity FM/FEk/1 Queuing Performance Using Fuzzy Queuing Model and Intuitionistic Fuzzy Queuing Model with Erlang Service Rates 基于模糊排队模型和基于Erlang服务率的直觉模糊排队模型的无限容量FM/FEk/1排队性能比较

IF 1.5

Pakistan Journal of Statistics and Operation Research Pub Date : 2023-03-06 DOI: 10.18187/pjsor.v19i1.4055

A. S, M. Shanmugasundari

{"title":"Comparison of Infinite Capacity FM/FEk/1 Queuing Performance Using Fuzzy Queuing Model and Intuitionistic Fuzzy Queuing Model with Erlang Service Rates","authors":"A. S, M. Shanmugasundari","doi":"10.18187/pjsor.v19i1.4055","DOIUrl":"https://doi.org/10.18187/pjsor.v19i1.4055","url":null,"abstract":"In this work, we suggest an analytic technique with triangular fuzzy and triangular intuitionistic fuzzy numbers to compute the membership functions of considerable state-executing proportion in Erlang service models. The inter-entry rate, which is Poisson, and the admin (service) rate, which is Erlang, are both fuzzy-natured in this case, with FEk designating the Erlang probabilistic deviation with k exponentially phase. The numeric antecedents are shown to validate the model's plausibility, FM/FEk/1. A contextual inquiry is also carried out, comparing individual fuzzy figures. Intuitionistic fuzzy queueing models that are comprehensible are more categorical than fuzzy queueing models. Expanding the fuzzy queuing model to an intuitionistic fuzzy environment can boost the implementation of the queuing model. The purpose of this study is to assess the performance of a single server Erlang queuing model with infinite capacity using fuzzy queuing theory and intuitionistic fuzzy queuing theory. The fuzzy queuing theory model's performance evaluations are reported as a range of outcomes, but the intuitionistic fuzzy queuing theory model provides a myriad of values. In this context, the arrival and the service rate are both triangular and intuitionistic triangular fuzzy numbers. An assessment is made to find evaluation criteria using a design protocol in which fuzzy values are kept as they are and not made into crisp values, and two statistical problems are solved to understand the existence of the method.","PeriodicalId":19973,"journal":{"name":"Pakistan Journal of Statistics and Operation Research","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47643007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of KLCI Index Through Economic LASSO Regression Model and Model Averaging 利用经济LASSO回归模型和模型平均预测KLCI指数

IF 1.5

Pakistan Journal of Statistics and Operation Research Pub Date : 2023-03-06 DOI: 10.18187/pjsor.v19i1.4214

Khuneswari Gopal Pillay, Soh Pei Lin

{"title":"Prediction of KLCI Index Through Economic LASSO Regression Model and Model Averaging","authors":"Khuneswari Gopal Pillay, Soh Pei Lin","doi":"10.18187/pjsor.v19i1.4214","DOIUrl":"https://doi.org/10.18187/pjsor.v19i1.4214","url":null,"abstract":"The Financial Times Stock Exchange (FTSE) Bursa Malaysia KLCI Index is a key component in the development of Malaysia's economic growth and the complexity in terms of identifying the factors that have a substantial impact on the Malaysian stock market has always been a contentious issue. In this study, the macroeconomic factors of exchange rate, interest rate, gold price, consumer price index, money supply M1, M2, and M3, industrial production, and oil price were discussed by using economic LASSO regression and Bayesian Model Averaging (BMA) with monthly average and monthly end time-series data spanning from January 2015 to June 2021, with a total of 78 observations by using the R Studio. The findings demonstrate that month-end data is better suited for stock market prediction than month-average data and that the BMA model is more suitable than the LASSO model, as seen by lower Mean Square Error of Prediction, MSE(P) and Residual Mean Square Error of Prediction, RMSE(P) values. The exchange rate, gold price, and money supply have a negative association with the dependent variables, while the consumer price index has a positive relationship associated with the dependent variables. The consumer price index is the most significant contributing factor, whereas gold price is the least significant. The result depicted that the KLCI index has no significant relationship with the variables interest rate, money supply M2, M1, industrial production index, and oil price. In conclusion, investors could specifically focus on the positive contributor and put lesser attention on improving their portfolio return.","PeriodicalId":19973,"journal":{"name":"Pakistan Journal of Statistics and Operation Research","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42257106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiclass Forecasting on Panel Data Using Autoregressive Multinomial Logit and C5.0 Decision Tree 基于自回归多项式Logit和C5.0决策树的面板数据多类预测

IF 1.5

Pakistan Journal of Statistics and Operation Research Pub Date : 2023-03-06 DOI: 10.18187/pjsor.v19i1.4053

Muhlis Ardiansyah, Hari Wijayanto, Anang Kurnia, A. Djuraidah

{"title":"Multiclass Forecasting on Panel Data Using Autoregressive Multinomial Logit and C5.0 Decision Tree","authors":"Muhlis Ardiansyah, Hari Wijayanto, Anang Kurnia, A. Djuraidah","doi":"10.18187/pjsor.v19i1.4053","DOIUrl":"https://doi.org/10.18187/pjsor.v19i1.4053","url":null,"abstract":"Panel data is commonly used for the numerical response variables, while the literature for forecasting categorical variables on the panel data structure is still challenging to find. Forecasting is important because it is helpful for government policies. This study aimed to forecast multiclass or categorical variables on the panel data structure. The proposed forecasting models were autoregressive multinomial logit and autoregressive C5.0. The strategy applied so that the two models could be used for forecasting was to add autoregressive effects and fixed predictor variables such as location, time, strata, and month of observations. The autoregressive effect was assumed to be a fixed effect and treated as a dummy variable. The data used was the category of land conditions through The Area Sampling Frame (ASF) survey conducted by the BPS-Statistics Indonesia. The evaluation of both models was based on classification and forecasting performance. Classification performance was obtained by dividing the dataset into 75% training data for modeling and 25% test data for validation and then repeated 200 times. The classification results showed that the autoregressive C5.0 accuracy was 86.48%, while the autoregressive multinomial logit was 83.97%. A comparison of forecasting performance was obtained by dividing the data into training and testing based on the time sequence. The result showed that the forecasting performance was worse than the classification performance. Autoregressive C5.0 had an accuracy of 77.43%, while autoregressive multinomial logit had 77.77%.","PeriodicalId":19973,"journal":{"name":"Pakistan Journal of Statistics and Operation Research","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47354077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Asymptotic Normality of the Conditional Hazard Rate Function Estimator for Right Censored Data under Association 关联条件下右截断数据条件危险率函数估计的渐近正态性

IF 1.5

Pakistan Journal of Statistics and Operation Research Pub Date : 2023-03-06 DOI: 10.18187/pjsor.v19i1.3740

Samra Dhiabi, Ourida Sadki

引用次数: 0