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The Ability of Artificial Neural Networks in Learning Dependency of Spatial Data‎ 人工神经网络在空间数据依赖性学习中的能力
Journal of Statistical Research of Iran Pub Date : 2019-09-01 DOI: 10.52547/jsri.16.1.211
A. Tavasoli, Y. Waghei, A. Nazemi
{"title":"The Ability of Artificial Neural Networks in Learning Dependency of Spatial Data‎","authors":"A. Tavasoli, Y. Waghei, A. Nazemi","doi":"10.52547/jsri.16.1.211","DOIUrl":"https://doi.org/10.52547/jsri.16.1.211","url":null,"abstract":"","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124464714","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
Some New Results on the Preservation of Stochastic Orders and Aging Classes under Random Minima and Maxima‎ 关于随机极小值和极大值下随机阶和老化类保持的一些新结果
Journal of Statistical Research of Iran Pub Date : 2019-09-01 DOI: 10.52547/jsri.16.1.143
Ebrahim Salehi, Ezzatollah Gholami
{"title":"Some New Results on the Preservation of Stochastic Orders and Aging Classes under Random Minima and Maxima‎","authors":"Ebrahim Salehi, Ezzatollah Gholami","doi":"10.52547/jsri.16.1.143","DOIUrl":"https://doi.org/10.52547/jsri.16.1.143","url":null,"abstract":"","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117136745","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 Quantile Approach to the Interval Shannon Entropy 区间香农熵的分位数法
Journal of Statistical Research of Iran Pub Date : 2019-03-10 DOI: 10.29252/jsri.15.2.317
M. Khorashadizadeh
{"title":"A Quantile Approach to the Interval Shannon Entropy","authors":"M. Khorashadizadeh","doi":"10.29252/jsri.15.2.317","DOIUrl":"https://doi.org/10.29252/jsri.15.2.317","url":null,"abstract":"","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115333606","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
On Properties of a Class of Bivariate FGM Type Distributions 一类二元FGM型分布的性质
Journal of Statistical Research of Iran Pub Date : 2019-03-10 DOI: 10.29252/jsri.15.2.300
Z. Sharifonnasabi, M. H. Alamatsaz, I. Kazemi
{"title":"On Properties of a Class of Bivariate FGM Type Distributions","authors":"Z. Sharifonnasabi, M. H. Alamatsaz, I. Kazemi","doi":"10.29252/jsri.15.2.300","DOIUrl":"https://doi.org/10.29252/jsri.15.2.300","url":null,"abstract":"","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128817219","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 Sample Size Determination for Joint Modeling of Longitudinal Measurements and Survival Data 纵向测量和生存数据联合建模的贝叶斯样本量确定
Journal of Statistical Research of Iran Pub Date : 2019-03-10 DOI: 10.29252/jsri.15.2.213
T. Baghfalaki
{"title":"Bayesian Sample Size Determination for Joint Modeling of Longitudinal Measurements and Survival Data","authors":"T. Baghfalaki","doi":"10.29252/jsri.15.2.213","DOIUrl":"https://doi.org/10.29252/jsri.15.2.213","url":null,"abstract":"A longitudinal study refers to collection of a response variable and possibly some explanatory variables at multiple follow-up times. In many clinical studies with longitudinal measurements, the response variable, for each patient is collected as long as an event of interest, which considered as clinical end point, occurs. Joint modeling of continuous longitudinal measurements and survival time is an approach for accounting association between two outcomes which frequently discussed in the literature, but design aspects of these models have been rarely considered. This paper uses a simulation-based method to determine the sample size from a Bayesian perspective. For this purpose, several Bayesian criteria for sample size determination are used, of which the most important one is the Bayesian power criterion (BPC), where the determined sample sizes are given based on BPC. We determine the sample size based on treatment effect on both outcomes (longitudinal measurements and survival time). The sample size determination is performed based on multiple hypotheses. Using several examples, the proposed Bayesian methods are illustrated and discussed. All the implementations are performed using R2OpenBUGS package and R 3.5.1 software.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128430943","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
Shrinkage and Bayesian Shrinkage Estimation of the Expected Length of a M/M/1 Queue System M/M/1队列系统预期长度的收缩和贝叶斯收缩估计
Journal of Statistical Research of Iran Pub Date : 2019-03-10 DOI: 10.29252/jsri.15.2.301
A. Kiapour, M. N. Qomi
{"title":"Shrinkage and Bayesian Shrinkage Estimation of the Expected Length of a M/M/1 Queue System","authors":"A. Kiapour, M. N. Qomi","doi":"10.29252/jsri.15.2.301","DOIUrl":"https://doi.org/10.29252/jsri.15.2.301","url":null,"abstract":"","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131144530","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
Assessment and Estimation of the Coefficients of a Linear Model for Interval Data 区间数据线性模型系数的评估与估计
Journal of Statistical Research of Iran Pub Date : 2019-03-10 DOI: 10.29252/jsri.15.2.237
Amir Massoud Malekfar, F. Eskandari
{"title":"Assessment and Estimation of the Coefficients of a Linear Model for Interval Data","authors":"Amir Massoud Malekfar, F. Eskandari","doi":"10.29252/jsri.15.2.237","DOIUrl":"https://doi.org/10.29252/jsri.15.2.237","url":null,"abstract":"","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114520325","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
Model Selection for Mixture Models Using Perfect Sample 完美样本混合模型的模型选择
Journal of Statistical Research of Iran Pub Date : 2019-03-01 DOI: 10.29252/jsri.15.2.173
S. Fallahigilan, A. Sayyareh
{"title":"Model Selection for Mixture Models Using Perfect Sample","authors":"S. Fallahigilan, A. Sayyareh","doi":"10.29252/jsri.15.2.173","DOIUrl":"https://doi.org/10.29252/jsri.15.2.173","url":null,"abstract":". We have considered a perfect sample method for model selection of finite mixture models with either known (fixed) or unknown number of components which can be applied in the most general setting with assumptions on the relation between the rival models and the true distribution. It is, both, one or neither to be well-specified or mis-specified, they may be nested or non-nested. We consider mixture distribution as a complete-data (bivariate) distribution by prediction of missing data variable (unobserved variable) and show that this ideas is applicable to use Vuong’s test for select optimum mixture model when number of components are known (fixed) or unknown. We have considered AIC and BIC based on the complete-data distribution. The performance of this method is evaluated by Monte-Carlo method and real data set, as Total Energy Production.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124286913","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
Inference for the Type-II Generalized Logistic Distribution with Progressive Hybrid Censoring 渐进式混合滤波下二类广义Logistic分布的推理
Journal of Statistical Research of Iran Pub Date : 2018-09-23 DOI: 10.29252/JSRI.14.2.189
M. Azizpour, A. Asgharzadeh
{"title":"Inference for the Type-II Generalized Logistic Distribution with Progressive Hybrid Censoring","authors":"M. Azizpour, A. Asgharzadeh","doi":"10.29252/JSRI.14.2.189","DOIUrl":"https://doi.org/10.29252/JSRI.14.2.189","url":null,"abstract":". This article presents the analysis of the Type-II hybrid progressively censored data when the lifetime distributions of the items follow Type-II generalized logistic distribution. Maximum likelihood estimators (MLEs) are investigated for estimating the location and scale parameters. It is observed that the MLEs can not be obtained in explicit forms. We provide the approximate maximum likelihood estimators (AMLEs) by appropriately approximating the likelihood equations. Asymptotic confidence intervals based on MLEs and AMLEs and one bootstrap confidence interval are proposed. Estimation of the shape parameter is also discussed. Monte Carlo simula-tions are performed to compare the performances of the different methods and two real data sets have been analyzed for illustrative purposes.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126383727","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
Prediction of Times to Failure of Censored Units in Progressive Hybrid Censored Samples for the Proportional Hazards Family 比例危害族渐进式混合截尾样本截尾单元失效时间的预测
Journal of Statistical Research of Iran Pub Date : 2018-09-23 DOI: 10.29252/jsri.14.2.131
Samaneh Ameli, Majid Rezaie, J. Ahmadi
{"title":"Prediction of Times to Failure of Censored Units in Progressive Hybrid Censored Samples for the Proportional Hazards Family","authors":"Samaneh Ameli, Majid Rezaie, J. Ahmadi","doi":"10.29252/jsri.14.2.131","DOIUrl":"https://doi.org/10.29252/jsri.14.2.131","url":null,"abstract":". In this paper, the problem of predicting times to failure of units censored in multiple stages of progressively hybrid censoring for the proportional hazards family is considered. We discuss different classical predictors. The best unbiased predictor ( BUP ), the maximum likelihood predictor ( MLP ) and conditional median predictor ( CMP ) are all derived. As an example, the obtained results are computed for exponential distribution. A numerical example is presented to illustrate the prediction methods discussed here. Using simulation studies, the predictors are compared in terms of bias and mean squared prediction error ( MSP E ).","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129091350","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
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