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Prediction Based on Type-II Censored Coherent System Lifetime Data under a Proportional Reversed Hazard Rate Model 比例反向危险率模型下基于II型截尾相干系统寿命数据的预测
IF 0.4
JIRSS-Journal of the Iranian Statistical Society Pub Date : 2021-06-01 DOI: 10.52547/jirss.20.1.153
A. Fallah, A. Asgharzadeh, H. Ng
{"title":"Prediction Based on Type-II Censored Coherent System Lifetime Data under a Proportional Reversed Hazard Rate Model","authors":"A. Fallah, A. Asgharzadeh, H. Ng","doi":"10.52547/jirss.20.1.153","DOIUrl":"https://doi.org/10.52547/jirss.20.1.153","url":null,"abstract":"In this paper, we discuss the prediction problem based on censored coherent system lifetime data when the system structure is known and the component lifetime follows the proportional reversed hazard model. Different point and interval predictors based on classical and Bayesian approaches are derived. A numerical example is presented to illustrate the prediction methods used in this paper. Monte Carlo simulation study is performed to evaluate and compare the performances of different prediction methods.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42101332","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 Policy Limit Allocations 关于策略极限分配的一些新结果
IF 0.4
JIRSS-Journal of the Iranian Statistical Society Pub Date : 2021-06-01 DOI: 10.52547/jirss.20.1.183
Sirous Fathi Manesh, Muhyiddin Izadi, Baha-Eldin Khaledi
{"title":"Some New Results on Policy Limit Allocations","authors":"Sirous Fathi Manesh, Muhyiddin Izadi, Baha-Eldin Khaledi","doi":"10.52547/jirss.20.1.183","DOIUrl":"https://doi.org/10.52547/jirss.20.1.183","url":null,"abstract":". Suppose that a policyholder faces n risks X 1 , . . . , X n which are insured under the policy limit with the total limit of l . Usually, the policyholder is asked to protect each X i with an arbitrary limit of l i such that (cid:80) ni = 1 l i = l . If the risks are independent and identically distributed with log-concave cumulative distribution function, using the notions of majorization and stochastic orderings, we prove that the equal limits provide the maximum of the expected utility of the wealth of policyholder. If the risks with log-concave distribution functions are independent and ordered in the sense of the reversed hazard rate order, we show that the equal limits is the most favourable allocation among the worst allocations. We also prove that if the joint probability density function is arrangement increasing, then the best arranged allocation maximizes the utility expectation of policyholder’s wealth. We apply the main results to the case when the risks are distributed according to a log-normal distribution. MSC: 60E15, 62P05.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43708063","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
An Alternative to the Beta-Binomial Distribution with Application in Developmental Toxicology 贝塔二项分布的一种替代方法及其在发育毒理学中的应用
IF 0.4
JIRSS-Journal of the Iranian Statistical Society Pub Date : 2021-06-01 DOI: 10.52547/jirss.20.1.333
M. Razzaghi
{"title":"An Alternative to the Beta-Binomial Distribution with Application in Developmental Toxicology","authors":"M. Razzaghi","doi":"10.52547/jirss.20.1.333","DOIUrl":"https://doi.org/10.52547/jirss.20.1.333","url":null,"abstract":". The beta-binomial distribution is resulted when the probability of success per trial in the binomial distribution varies in successive trials and the mixing distribution is from the beta family. For experiments with binary outcomes, often it may happen that observations exhibit some extra binomial variation and occur in clusters. In such experiments the beta-binomial distribution can generally provide an adequate fit to the data. Here, we introduce an alternative when the mixing distribution is assumed to be from the log-Lindley family. The properties of this new model are explored and it is shown that similar to the beta-binomial distribution, the log-Lindley binomial distribution can also be applied in modeling clustered binary outcomes. An example with real experimental data from a developmental toxicity experiment is utilized to provide further illustration.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44073207","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
Ageing Orders of Series-Parallel and Parallel-Series Systems with Independent Subsystems Consisting of Dependent Components 由相关部件组成的独立子系统的串并联和并串联系统的老化阶
IF 0.4
JIRSS-Journal of the Iranian Statistical Society Pub Date : 2021-06-01 DOI: 10.52547/jirss.20.1.83
N. Balakrishnan, G. Barmalzan, A. Hosseinzadeh
{"title":"Ageing Orders of Series-Parallel and Parallel-Series Systems with Independent Subsystems Consisting of Dependent Components","authors":"N. Balakrishnan, G. Barmalzan, A. Hosseinzadeh","doi":"10.52547/jirss.20.1.83","DOIUrl":"https://doi.org/10.52547/jirss.20.1.83","url":null,"abstract":". In this paper, we consider series-parallel and parallel-series systems with independent subsystems consisting of dependent homogeneous components whose joint lifetimes are modeled by an Archimedean copula. Then, by considering two such systems with di ff erent numbers of components within each subsystem, we establish hazard rate and reversed hazard rate orderings between the two system lifetimes, and also discuss how these systems age relative to each other in terms of hazard rate and reversed hazard rate functions.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44398768","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
Asymmetric Univariate and Bivariate Laplace and Generalized Laplace Distributions 非对称单变量和双变量拉普拉斯和广义拉普拉斯分布
IF 0.4
JIRSS-Journal of the Iranian Statistical Society Pub Date : 2021-06-01 DOI: 10.52547/jirss.20.1.61
B. Arnold, Matthew A. Arvanitis
{"title":"Asymmetric Univariate and Bivariate Laplace and Generalized Laplace Distributions","authors":"B. Arnold, Matthew A. Arvanitis","doi":"10.52547/jirss.20.1.61","DOIUrl":"https://doi.org/10.52547/jirss.20.1.61","url":null,"abstract":". Alternative specifications of univariate asymmetric Laplace models are described and investigated. A more general mixture model is then introduced. Bivariate extensions of these models are discussed in some detail, with particular emphasis on associated parameter estimation strategies. Multivariate versions of the models are briefly introduced.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49132550","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
Applications of TP2 Functions in Theory of Stochastic Orders: A Review of some Useful Results TP2函数在随机序理论中的应用——对一些有用结果的评述
IF 0.4
JIRSS-Journal of the Iranian Statistical Society Pub Date : 2021-06-01 DOI: 10.52547/jirss.20.1.269
Sameen Naqvi, N. Misra, P. Chan
{"title":"Applications of TP2 Functions in Theory of Stochastic Orders: A Review of some Useful Results","authors":"Sameen Naqvi, N. Misra, P. Chan","doi":"10.52547/jirss.20.1.269","DOIUrl":"https://doi.org/10.52547/jirss.20.1.269","url":null,"abstract":"","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42989177","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
Conditional Dependence in Longitudinal Data Analysis 纵向数据分析中的条件依赖性
IF 0.4
JIRSS-Journal of the Iranian Statistical Society Pub Date : 2021-06-01 DOI: 10.52547/jirss.20.1.347
M. Torabi, A. R. Leon
{"title":"Conditional Dependence in Longitudinal Data Analysis","authors":"M. Torabi, A. R. Leon","doi":"10.52547/jirss.20.1.347","DOIUrl":"https://doi.org/10.52547/jirss.20.1.347","url":null,"abstract":". Mixed models are widely used to analyze longitudinal data. In their conventional formulation as linear mixed models (LMMs) and generalized LMMs (GLMMs), a commonly indispensable assumption in settings involving longitudinal non-Gaussian data is that the longitudinal observations from subjects are conditionally independent, given subject-specific random e ff ects. Although conventional Gaussian LMMs are able to incorporate conditional dependence of longitudinal observations, they require that the data are, or some transformation of them is, Gaussian, a serious limitation in a wide variety of practical applications. Here, we introduce the class of Gaussian copula conditional regression models (GCCRMs) as flexible alternatives to conventional LMMs and GLMMs. One advantage of GCCRMs is that they extend conventional LMMs and GLMMs in a way that reduces to conventional LMMs, when the data are Gaussian, and to conventional GLMMs, when conditional independence is assumed. We implement likelihood analysis of GCCRMs using existing software and statistical packages and evaluate the finite-sample performance of maximum likelihood estimates for GCCRM empirically via simulations vis-à-vis the ‘naive’ likelihood analysis that incorrectly assumes conditionally independent longitudinal data. Our results show that the ‘naive’ analysis yields estimates with possibly severe bias and incorrect standard errors, leading to misleading inferences. We use bolus count data on patients’ controlled analgesia comparing dosing regimes and data on serum creatinine from a renal graft study to illustrate the applications of GCCRMs.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45827870","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
Kernel Ridge Estimator for the Partially Linear Model under Right-Censored Data 右截尾数据下部分线性模型的核岭估计
IF 0.4
JIRSS-Journal of the Iranian Statistical Society Pub Date : 2021-06-01 DOI: 10.52547/jirss.20.1.1
S. E. Ahmed, D. Aydın, E. Yılmaz
{"title":"Kernel Ridge Estimator for the Partially Linear Model under Right-Censored Data","authors":"S. E. Ahmed, D. Aydın, E. Yılmaz","doi":"10.52547/jirss.20.1.1","DOIUrl":"https://doi.org/10.52547/jirss.20.1.1","url":null,"abstract":"Objective: This paper aims to introduce a modified kernel-type ridge estimator for partially linear models under randomly-right censored data. Such models include two main issues that need to be solved: multi-collinearity and censorship. To address these issues, we improved the kernel estimator based on synthetic data transformation and kNN imputation techniques. The key idea of this paper is to obtain a satisfactory estimate of the partially linear model with multi-collinear and right-censored using a modified ridge estimator. Results: To determine the performance of the method, a detailed simulation study is carried out and a kernel-type ridge estimator for PLM is investigated for two censorship solution techniques. The results are compared and presented with tables and figures. Necessary derivations for the modified semiparametric estimator are given in appendices.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44308093","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
Stage Life Testing with Missing Stage Information - an EM-Algorithm Approach 缺少阶段信息的阶段寿命测试——一种EM算法
IF 0.4
JIRSS-Journal of the Iranian Statistical Society Pub Date : 2021-06-01 DOI: 10.52547/jirss.20.1.123
E. Cramer, B. Laumen
{"title":"Stage Life Testing with Missing Stage Information - an EM-Algorithm Approach","authors":"E. Cramer, B. Laumen","doi":"10.52547/jirss.20.1.123","DOIUrl":"https://doi.org/10.52547/jirss.20.1.123","url":null,"abstract":". We consider a stage life testing model and assume that the information at which levels the failures occurred is not available. In order to find estimates for the lifetime distribution parameters, we propose an EM-algorithm approach which interprets the lack of knowledge about the stages as missing information. Furthermore, we illustrate the implementation di ffi culties caused by an increasing number of stages. The study is supplemented by a data example as well as simulations.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48055837","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
Matrix-Variate Beta Generator - Developments and Application 矩阵变分贝塔生成器的发展与应用
IF 0.4
JIRSS-Journal of the Iranian Statistical Society Pub Date : 2021-06-01 DOI: 10.52547/jirss.20.1.289
J. V. Niekerk, A. Bekker, M. Arashi
{"title":"Matrix-Variate Beta Generator - Developments and Application","authors":"J. V. Niekerk, A. Bekker, M. Arashi","doi":"10.52547/jirss.20.1.289","DOIUrl":"https://doi.org/10.52547/jirss.20.1.289","url":null,"abstract":". Matrix-variate beta distributions are applied in di ff erent fields of hypothesis testing, multivariate correlation analysis, zero regression, canonical correlation analysis and etc. A methodology is proposed to generate matrix-variate beta generator distributions by combining the matrix-variate beta kernel with an unknown function of the trace operator. Several statistical characteristics, extensions and developments are presented. Special members are then used in a univariate and multivariate Bayesian analysis setting. These models are fitted to simulated and real datasets, and their fitting and performance are compared to well-established competitors.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49502438","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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