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Journal of Modern Applied Statistical Methods最新文献

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JMASM 55: MATLAB Algorithms and Source Codes of 'cbnet' Function for Univariate Time Series Modeling with Neural Networks (MATLAB) JMASM 55：用神经网络（MATLAB）进行单变量时间序列建模的“cbnet”函数的MATLAB算法和源代码
Journal of Modern Applied Statistical Methods Pub Date : 2021-09-28 DOI: 10.22237/jmasm/1608553080
Cagatay Bal, S. Demir
{"title":"JMASM 55: MATLAB Algorithms and Source Codes of 'cbnet' Function for Univariate Time Series Modeling with Neural Networks (MATLAB)","authors":"Cagatay Bal, S. Demir","doi":"10.22237/jmasm/1608553080","DOIUrl":"https://doi.org/10.22237/jmasm/1608553080","url":null,"abstract":"Artificial Neural Networks (ANN) can be designed as a nonparametric tool for time series modeling. MATLAB serves as a powerful environment for ANN modeling. Although Neural Network Time Series Tool (ntstool) is useful for modeling time series, more detailed functions could be more useful in order to get more detailed and comprehensive analysis results. For these purposes, cbnet function with properties such as input lag generator, step-ahead forecaster, trial-error based network selection strategy, alternative network selection with various performance measure and global repetition feature to obtain more alternative network has been developed, and MATLAB algorithms and source codes has been introduced. A detailed comparison with the ntstool is carried out, showing that the cbnet function covers the shortcomings of ntstool.","PeriodicalId":47201,"journal":{"name":"Journal of Modern Applied Statistical Methods","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49357272","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
Bayesian Sensitivity-Specificity and ROC Analysis for Finding Key Drivers 寻找关键驱动因素的贝叶斯敏感性特异性和ROC分析
Journal of Modern Applied Statistical Methods Pub Date : 2021-08-31 DOI: 10.22237/jmasm/1619481960
S. Lipovetsky, Michael Conklin
{"title":"Bayesian Sensitivity-Specificity and ROC Analysis for Finding Key Drivers","authors":"S. Lipovetsky, Michael Conklin","doi":"10.22237/jmasm/1619481960","DOIUrl":"https://doi.org/10.22237/jmasm/1619481960","url":null,"abstract":"Finding key drivers in regression modeling via Bayesian Sensitivity-Specificity and Receiver Operating Characteristic is suggested, and clearly interpretable results are obtained. Numerical comparisons with other techniques show that this methodology can be useful in practical statistical modeling and analysis helping to researchers and managers in making meaningful decisions.","PeriodicalId":47201,"journal":{"name":"Journal of Modern Applied Statistical Methods","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41410921","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: 4
Pairwise Balanced Designs From Cyclic PBIB Designs 循环PBIB设计中的成对平衡设计
Journal of Modern Applied Statistical Methods Pub Date : 2021-06-08 DOI: 10.22237/JMASM/1608552960
D. K. Ghosh, N. R. Desai, Shreya Ghosh
{"title":"Pairwise Balanced Designs From Cyclic PBIB Designs","authors":"D. K. Ghosh, N. R. Desai, Shreya Ghosh","doi":"10.22237/JMASM/1608552960","DOIUrl":"https://doi.org/10.22237/JMASM/1608552960","url":null,"abstract":"A pairwise balanced designs was constructed using cyclic partially balanced incomplete block designs with either (λ1 – λ2) = 1 or (λ2 – λ1) = 1. This method of construction of Pairwise balanced designs is further generalized to construct it using cyclic partially balanced incomplete block design when |(λ1 – λ2)| = p. The methods of construction of pairwise balanced designs was supported with examples. A table consisting parameters of Cyclic PBIB designs and its corresponding constructed pairwise balanced design is also included.","PeriodicalId":47201,"journal":{"name":"Journal of Modern Applied Statistical Methods","volume":"19 1","pages":"2"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46455849","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
On the Level of Precision of a Heterogeneous Transfer Function in a Statistical Neural Network Model 统计神经网络模型中异构传递函数的精度水平
Journal of Modern Applied Statistical Methods Pub Date : 2021-06-08 DOI: 10.22237/JMASM/1608553560
C. Udomboso
{"title":"On the Level of Precision of a Heterogeneous Transfer Function in a Statistical Neural Network Model","authors":"C. Udomboso","doi":"10.22237/JMASM/1608553560","DOIUrl":"https://doi.org/10.22237/JMASM/1608553560","url":null,"abstract":"A heterogeneous function of the statistical neural network is presented from two transfer functions: symmetric saturated linear and hyperbolic tangent sigmoid. The precision of the derived heterogeneous model over their respective homogeneous forms are established, both at increased sample sizes hidden neurons. Results further show the sensitivity of the heterogeneous model to increase in hidden neurons.","PeriodicalId":47201,"journal":{"name":"Journal of Modern Applied Statistical Methods","volume":"19 1","pages":"2-16"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44832021","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 New Generalized Family of Distributions for Lifetime Data 寿命数据的一种新的广义分布族
Journal of Modern Applied Statistical Methods Pub Date : 2021-06-08 DOI: 10.22237/JMASM/1608553200
Maha A. Aldahlan, Mohamed G. Khalil, A. Afify
{"title":"A New Generalized Family of Distributions for Lifetime Data","authors":"Maha A. Aldahlan, Mohamed G. Khalil, A. Afify","doi":"10.22237/JMASM/1608553200","DOIUrl":"https://doi.org/10.22237/JMASM/1608553200","url":null,"abstract":"A new class of continuous distributions called the generalized Burr X-G family is introduced. Some special models of the new family are provided. Some of its mathematical properties including explicit expressions for the quantile and generating functions, ordinary and incomplete moments, order statistics and Rényi entropy are derived. The maximum likelihood is used for estimating the model parameters. The flexibility of the generated family is illustrated by means of two applications to real data sets.","PeriodicalId":47201,"journal":{"name":"Journal of Modern Applied Statistical Methods","volume":"19 1","pages":"2-23"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41852211","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: 3
A New Right-Skewed Upside Down Bathtub Shaped Heavy-tailed Distribution and its Applications 一种新的右斜上下浴缸形重尾分布及其应用
Journal of Modern Applied Statistical Methods Pub Date : 2021-06-08 DOI: 10.22237/JMASM/1608552600
S. Maurya, S. Singh, U. Singh
{"title":"A New Right-Skewed Upside Down Bathtub Shaped Heavy-tailed Distribution and its Applications","authors":"S. Maurya, S. Singh, U. Singh","doi":"10.22237/JMASM/1608552600","DOIUrl":"https://doi.org/10.22237/JMASM/1608552600","url":null,"abstract":"A one parameter right skewed, upside down bathtub type, heavy-tailed distribution is derived. Various statistical properties and maximum likelihood approaches for estimation purpose are studied. Five different real data sets with four different models are considered to illustrate the suitability of the proposed model.","PeriodicalId":47201,"journal":{"name":"Journal of Modern Applied Statistical Methods","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44778763","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: 3
VIF-Regression Screening Ultrahigh Dimensional Feature Space VIF回归筛选超高维特征空间
Journal of Modern Applied Statistical Methods Pub Date : 2021-06-08 DOI: 10.22237/JMASM/1608553020
Hassan S. Uraibi
{"title":"VIF-Regression Screening Ultrahigh Dimensional Feature Space","authors":"Hassan S. Uraibi","doi":"10.22237/JMASM/1608553020","DOIUrl":"https://doi.org/10.22237/JMASM/1608553020","url":null,"abstract":"Iterative Sure Independent Screening (ISIS) was proposed for the problem of variable selection with ultrahigh dimensional feature space. Unfortunately, the ISIS method transforms the dimensionality of features from ultrahigh to ultra-low and may result in un-reliable inference when the number of important variables particularly is greater than the screening threshold. The proposed method has transformed the ultrahigh dimensionality of features to high dimension space in order to remedy of losing some information by ISIS method. The proposed method is compared with ISIS method by using real data and simulation. The results show this method is more efficient and more reliable than ISIS method.","PeriodicalId":47201,"journal":{"name":"Journal of Modern Applied Statistical Methods","volume":"19 1","pages":"3"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49287913","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
JMASM 57: Bayesian Survival Analysis of Lomax Family Models with Stan (R) JMASM 57：具有Stan（R）的Lomax家族模型的贝叶斯生存分析
Journal of Modern Applied Statistical Methods Pub Date : 2021-06-08 DOI: 10.22237/JMASM/1608553800
Mohammed H. A. AbuJarad, A. A. Khan
{"title":"JMASM 57: Bayesian Survival Analysis of Lomax Family Models with Stan (R)","authors":"Mohammed H. A. AbuJarad, A. A. Khan","doi":"10.22237/JMASM/1608553800","DOIUrl":"https://doi.org/10.22237/JMASM/1608553800","url":null,"abstract":"An attempt is made to fit three distributions, the Lomax, exponential Lomax, and Weibull Lomax to implement Bayesian methods to analyze Myeloma patients using Stan. This model is applied to a real survival censored data so that all the concepts and computations will be around the same data. A code was developed and improved to implement censored mechanism throughout using rstan. Furthermore, parallel simulation tools are also implemented with an extensive use of rstan.","PeriodicalId":47201,"journal":{"name":"Journal of Modern Applied Statistical Methods","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46965283","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
Two Different Classes of Shrinkage Estimators for the Scale Parameter of the Rayleigh Distribution 瑞利分布尺度参数的两种不同的收缩估计器
Journal of Modern Applied Statistical Methods Pub Date : 2021-06-08 DOI: 10.22237/JMASM/1608553440
Talha Omer, Zawar Hussain, Muhammad Qasim, Said Farooq Shah, Akbar Ali Khan
{"title":"Two Different Classes of Shrinkage Estimators for the Scale Parameter of the Rayleigh Distribution","authors":"Talha Omer, Zawar Hussain, Muhammad Qasim, Said Farooq Shah, Akbar Ali Khan","doi":"10.22237/JMASM/1608553440","DOIUrl":"https://doi.org/10.22237/JMASM/1608553440","url":null,"abstract":"Shrinkage estimators are introduced for the scale parameter of the Rayleigh distribution by using two different shrinkage techniques. The mean squared error properties of the proposed estimator have been derived. The comparison of proposed classes of the estimators is made with the respective conventional unbiased estimators by means of mean squared error in the simulation study. Simulation results show that the proposed shrinkage estimators yield smaller mean squared error than the existence of unbiased estimators.","PeriodicalId":47201,"journal":{"name":"Journal of Modern Applied Statistical Methods","volume":"19 1","pages":"2-21"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43636452","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
Generalized Ratio-cum-Product Estimator for Finite Population Mean under Two-Phase Sampling Scheme 两阶段抽样方案下有限总体均值的广义比值积估计
Journal of Modern Applied Statistical Methods Pub Date : 2021-06-08 DOI: 10.22237/JMASM/1608553320
G. Vishwakarma, S. Zeeshan
{"title":"Generalized Ratio-cum-Product Estimator for Finite Population Mean under Two-Phase Sampling Scheme","authors":"G. Vishwakarma, S. Zeeshan","doi":"10.22237/JMASM/1608553320","DOIUrl":"https://doi.org/10.22237/JMASM/1608553320","url":null,"abstract":"A method to lower the MSE of a proposed estimator relative to the MSE of the linear regression estimator under two-phase sampling scheme is developed. Estimators are developed to estimate the mean of the variate under study with the help of auxiliary variate (which are unknown but it can be accessed conveniently and economically). The mean square errors equations are obtained for the proposed estimators. In addition, optimal sample sizes are obtained under the given cost function. The comparison study has been done to set up conditions for which developed estimators are more effective than other estimators with novelty. The empirical study is also performed to supplement the claim that the developed estimators are more efficient.","PeriodicalId":47201,"journal":{"name":"Journal of Modern Applied Statistical Methods","volume":" ","pages":"2-16"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46665334","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: 3
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