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Austrian Journal of Statistics最新文献

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A Joint Multiresponse Split-Plot Modeling and Optimization Including Fixed and Random Effects 包含固定和随机效应的联合多响应分割图建模与优化
IF 0.6
Austrian Journal of Statistics Pub Date : 2022-01-24 DOI: 10.17713/ajs.v51i1.1211
R. Berni, N. D. Nikiforova
{"title":"A Joint Multiresponse Split-Plot Modeling and Optimization Including Fixed and Random Effects","authors":"R. Berni, N. D. Nikiforova","doi":"10.17713/ajs.v51i1.1211","DOIUrl":"https://doi.org/10.17713/ajs.v51i1.1211","url":null,"abstract":"This paper deals with a proposal for joint modeling and process optimization for split-plot designs analyzed through mixed response surface models. It addresses the following main issues: i) the building of a joint mixed responsesurface model for a multiple response situation, by defining only one response through which specific coefficients areincluded for studying the association among the responses; ii) the considering of fixed as well as random effects within a joint modeling and optimization context; iii) the achievement of an optimal solution by involving specific as well as common coefficients for the responses. We illustrate our contribution through a case-study related to a split-plot design on electronic components of printed circuit boards (PCBs); we obtain satisfactory results by confirming the validity of thiscontribution, where the qualitative factor PCB is also studied and optimized.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"67 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2022-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73116475","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
Assessing Performance of the Generalized Exponential Model in the Presence of the Interval Censored Data with Covariate 具有协变量的区间截尾数据下广义指数模型的性能评价
IF 0.6
Austrian Journal of Statistics Pub Date : 2022-01-24 DOI: 10.17713/ajs.v51i1.1192
Nada Alharbi, Jayanthi A., H. A., W. Ling
{"title":"Assessing Performance of the Generalized Exponential Model in the Presence of the Interval Censored Data with Covariate","authors":"Nada Alharbi, Jayanthi A., H. A., W. Ling","doi":"10.17713/ajs.v51i1.1192","DOIUrl":"https://doi.org/10.17713/ajs.v51i1.1192","url":null,"abstract":"This study aims to extend the generalized exponential model (GEM) to include covariates in the presence of interval-censored data. The maximum likelihood estimator (MLE) was obtained for the parameter of the model formulated. Afterward, a thorough simulation study was carried out to evaluate the estimator's performance based on the values of bias, standard error (SE), and root mean square error (RMSE). The result indicated that the (SE) and (RMSE) decrease with the increase in sample sizes and decrease in censoring proportions. Finally, the performance of the Wald confidence interval estimation technique for the GE model with interval-censored data covariate was assessed by a coverage probability study at several censoring proportions and different sample sizes.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"15 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2022-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78285495","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
Analyzing Overdispersed Antenatal Care Count Data in Bangladesh: Mixed Poisson Regression with Individual-Level Random Effects 分析孟加拉国过度分散的产前护理计数数据:混合泊松回归与个体水平随机效应
IF 0.6
Austrian Journal of Statistics Pub Date : 2021-07-15 DOI: 10.17713/AJS.V50I4.1163
Z. Hossain, Maria
{"title":"Analyzing Overdispersed Antenatal Care Count Data in Bangladesh: Mixed Poisson Regression with Individual-Level Random Effects","authors":"Z. Hossain, Maria","doi":"10.17713/AJS.V50I4.1163","DOIUrl":"https://doi.org/10.17713/AJS.V50I4.1163","url":null,"abstract":"Poisson regression (PR) is commonly used as the base model for analyzing count data with the restrictive equidispersion property. However, overdispersed nature of count data is very common in health sciences. In such cases, PR produces misleading inferences and hence give incorrect interpretations of the results. Mixed Poisson regression with individual--level random effects (MPR_ILRE) is a further improvement for analyzing such data. We compare MPR_ILRE with PR, quasi-Poisson regression (Q_PR) and negative binomial regression (NBR) for modelling overdispersed antenatal care (ANC) count data extracted from the latest Bangladesh Demographic and Health Survey (BDHS) 2014. MPR_ILRE is found to be the best choice because of its minimum Akaike information criterion (AIC) value and the overdispersion exists in data has also been modelled very well. Study findings reveal that on average, women attended less than three ANC visits and only 6.5% women received the World Health Organization (WHO) recommended eight or more ANC visits for the safe pregnancy and child birth. Administrative division, place of residence, birth order, exposure of media, education, wealth index and body mass index (BMI) have significant impact on adequate ANC attendance of women to reducing pregnancy complications, maternal and child deaths in Bangladesh.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"C-20 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85067872","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: 2
GARCH Models under Power Transformed Returns: Empirical Evidence from International Stock Indices 权力转换收益下的GARCH模型:来自国际股票指数的经验证据
IF 0.6
Austrian Journal of Statistics Pub Date : 2021-07-15 DOI: 10.17713/AJS.V50I4.1075
D. Nugroho, Tundjung Mahatma, Yulius Pratomo
{"title":"GARCH Models under Power Transformed Returns: Empirical Evidence from International Stock Indices","authors":"D. Nugroho, Tundjung Mahatma, Yulius Pratomo","doi":"10.17713/AJS.V50I4.1075","DOIUrl":"https://doi.org/10.17713/AJS.V50I4.1075","url":null,"abstract":"This study evaluates the empirical performance of four power transformation families: extended Tukey, Modulus, Exponential, and Yeo--Johnson, in modeling the return in the context of GARCH(1,1) models with two error distributions: Gaussian (normal) and Student-t. We employ an Adaptive Random Walk Metropolis method in Markov Chain Monte Carlo scheme to draw parameters. Using 19 international stock indices from the Oxford-Man Institute and basing on the log likelihood, Akaike Information Criterion, Bayesian Information Criterion, and Deviance Information Criterion, the use of power transformation families to the return series clearly improves the fit of the normal GARCH(1,1) model. In particular, the Modulus transformation family provides the best fit. Under Student's t-error distribution assumption, the GARCH(1,1) models under power transformed returns perform better in few cases.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"92 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79424202","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 Generalized Estimating Equations Approach for Modeling Spatially Clustered Data 空间聚类数据建模的广义估计方程方法
IF 0.6
Austrian Journal of Statistics Pub Date : 2021-07-15 DOI: 10.17713/AJS.V50I4.1097
Nasrin Lipi, Mohammad Samsul Alam, S. S. Hossain
{"title":"A Generalized Estimating Equations Approach for Modeling Spatially Clustered Data","authors":"Nasrin Lipi, Mohammad Samsul Alam, S. S. Hossain","doi":"10.17713/AJS.V50I4.1097","DOIUrl":"https://doi.org/10.17713/AJS.V50I4.1097","url":null,"abstract":"Clustering in spatial data is very common phenomena in various fields such as disease mapping, ecology, environmental science and so on. Analysis of spatially clustered data should be different from conventional analysis of spatial data because of the nature of clusters in the data. Because it is expected that the observations of same cluster are more similar than the observations from different clusters. In this study, a method has been proposed for the analysis of spatially clustered areal data based on generalized estimating equations which were originally developed for analyzing longitudinal data. The performance of the model for known clusters is tested in terms of how well it estimates the regression parameters and how well it captures the true spatial process. These results are presented and compared with the conditional auto-regressive model which is the most frequently used spatial model. In the simulation study, the proposed generalized estimating equations approach yields better results than the popular conditional auto-regressive model from the both perspectives of parameter estimation and spatial process capturing. A real life data on the vitamin A supplement coverage among postpartum women in Bangladesh is then analyzed for demonstration of the method. The existing divisional clustering behavior of vitamin A supplement coverage in Bangladesh is identified more accurately by the proposed approach than that by the conditional auto-regressive model.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"61 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90288557","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
Two-sample Tests for Functional Data Using Characteristic Functions 使用特征函数的功能数据的双样本测试
IF 0.6
Austrian Journal of Statistics Pub Date : 2021-07-15 DOI: 10.17713/AJS.V50I4.1099
M. Krzyśko, Łukasz Smaga
{"title":"Two-sample Tests for Functional Data Using Characteristic Functions","authors":"M. Krzyśko, Łukasz Smaga","doi":"10.17713/AJS.V50I4.1099","DOIUrl":"https://doi.org/10.17713/AJS.V50I4.1099","url":null,"abstract":"In this paper, we consider the two-sample problem for univariate and multivariate functional data. To solve this problem, we use tool of characteristic function and a basis function representation of functional data. We construct test statistics for conformity of distributions based on a weighted distance between characteristic functions of random vectors obtained in basis representation. Different weight functions result in different test statistics, whose distributions are approximated by permutation method. Testing procedures are implemented in the R program and the code is available. Simulation study shows good finite sample properties of proposed methods, while real data example illustrates the application of them.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"13 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78274189","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
New Distribution for Fitting Discrete Data: The Poisson-Gold Distribution and Its Statistical Properties 离散数据拟合的新分布:泊松-金分布及其统计性质
IF 0.6
Austrian Journal of Statistics Pub Date : 2021-07-15 DOI: 10.17713/AJS.V50I4.1091
A. Hanandeh, Amjad D. Al-Nasser
{"title":"New Distribution for Fitting Discrete Data: The Poisson-Gold Distribution and Its Statistical Properties","authors":"A. Hanandeh, Amjad D. Al-Nasser","doi":"10.17713/AJS.V50I4.1091","DOIUrl":"https://doi.org/10.17713/AJS.V50I4.1091","url":null,"abstract":"Motivated mainly by lifetime issues, a new lifetime distribution coined ``Discrete Poisson-Gold distribution'' is introduced in this paper. Different structural properties of the new distribution are derived including moment generating function and the $r^{th}$ moment and others are presented. In addition, we discussed various important mathematical properties of the new distribution including estimation procedures for estimating the distribution parameters using the maximum likelihood and method of moments. The usefulness and credibility of the distribution are illustrated by means of two real-data applications to show its superior performance over some other well-known lifetime distributions and to prove its versatility in practical applications.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"12 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81900667","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: 2
New Developments on the Non-Central Chi-Squared and Beta Distributions 非中心卡方分布和Beta分布的新进展
IF 0.6
Austrian Journal of Statistics Pub Date : 2021-07-14 DOI: 10.17713/ajs.v51i1.1106
C. Orsi
{"title":"New Developments on the Non-Central Chi-Squared and Beta Distributions","authors":"C. Orsi","doi":"10.17713/ajs.v51i1.1106","DOIUrl":"https://doi.org/10.17713/ajs.v51i1.1106","url":null,"abstract":"New formulas for the moments about zero of the Non-central Chi-Squared and the Non-central Beta distributions are achieved by means of novel approaches. The mixture representation of the former model and a new expansion of the ascending factorial of a binomial are the main ingredients of the first approach, whereas the second one hinges on an interesting relationship of conditional independence and a simple conditional density of the latter model. Then, a simulation study is carried out in order to pursue a twofold purpose: providing numerical validations of the derived moment formulas on one side and discussing the advantages of the new formulas over the existing ones on the other.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"3 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79509305","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: 2
A Global Bayes Factor for Observations on an Infinite-Dimensional Hilbert Space, Applied to Signal Detection in fMRI 无限维Hilbert空间观测的全局Bayes因子，应用于fMRI信号检测
IF 0.6
Austrian Journal of Statistics Pub Date : 2021-07-05 DOI: 10.17713/AJS.V50I3.1050
K. Shafie, Mohammad Reza Faridrohani, S. Noorbaloochi, H. Rekabdarkolaee
{"title":"A Global Bayes Factor for Observations on an Infinite-Dimensional Hilbert Space, Applied to Signal Detection in fMRI","authors":"K. Shafie, Mohammad Reza Faridrohani, S. Noorbaloochi, H. Rekabdarkolaee","doi":"10.17713/AJS.V50I3.1050","DOIUrl":"https://doi.org/10.17713/AJS.V50I3.1050","url":null,"abstract":"Functional Magnetic Resonance Imaging (fMRI) is a fundamental tool in advancing our understanding of the brain's functionality. Recently, a series of Bayesian approaches have been suggested to test for the voxel activation in different brain regions. In this paper, we propose a novel definition for the global Bayes factor to test for activation using the Radon-Nikodym derivative. Our proposed method extends the definition of Bayes factor to an infinite dimensional Hilbert space. Using this extended definition, a Bayesian testing procedure is introduced for signal detection in noisy images when both signal and noise are considered as an element of an infinite dimensional Hilbert space. This new approach is illustrated through a real data analysis to find activated areas of Brain in an fMRI data.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"73 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82370432","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
Comparative Performance of Three Methods to Classify Smokers Data 三种吸烟者数据分类方法的性能比较
IF 0.6
Austrian Journal of Statistics Pub Date : 2021-07-05 DOI: 10.17713/AJS.V50I3.1013
Amenah Al-Najafi
{"title":"Comparative Performance of Three Methods to Classify Smokers Data","authors":"Amenah Al-Najafi","doi":"10.17713/AJS.V50I3.1013","DOIUrl":"https://doi.org/10.17713/AJS.V50I3.1013","url":null,"abstract":"Since recently tobacco epidemic is one of the most important health hazards that face Iraqi individuals and communities in spite of the large information supported by the Iraqi Ministry of Health and the available statistics that link smoking with many life threatening illnesses to human. Tobacco consumption rates are increasing nowadays among university students. Iraqi Ministry of Health confirmed the need to take a serious action to support research that examines the tobacco epidemic among students, in an attempt to find the causes and the appropriate solutions.It is, therefore, our main objective is to investigate the student smokers from the University of Kufa in Iraq. The research attempted to study the behaviour of smokers using questionnaires. The performance of Latent Classes (LC) is evaluated by attempting to classify the student smokers and then compared it to two clustering methods namely K-means and Two-Step method.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"8 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81394633","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
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