Austrian Journal of Statistics最新文献_第10页

On the Estimation Problems for Exponentiated Exponential Distribution under Generalized Progressive Hybrid Censoring 广义渐进混合滤波下指数分布的估计问题

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Austrian Journal of Statistics Pub Date : 2021-02-03 DOI: 10.17713/AJS.V50I1.952

Aakriti Pandey, A. Kaushik, S. Singh, U. Singh

引用次数: 2

Modified Likelihood Ratio Test for Sub-mean Vectors with Two-step Monotone Missing Data in Two-sample Problem 双样本问题中两步单调缺失亚均值向量的改进似然比检验

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Austrian Journal of Statistics Pub Date : 2021-02-03 DOI: 10.17713/AJS.V50I1.928

Tamae Kawasaki, T. Seo

引用次数: 0

Robust Estimation for a Generalised Ratio Model 广义比率模型的鲁棒估计

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Austrian Journal of Statistics Pub Date : 2021-02-03 DOI: 10.17713/AJS.V50I1.994

Kazumichi Wada, Keiichiro Sakashita, H. Tsubaki

{"title":"Robust Estimation for a Generalised Ratio Model","authors":"Kazumichi Wada, Keiichiro Sakashita, H. Tsubaki","doi":"10.17713/AJS.V50I1.994","DOIUrl":"https://doi.org/10.17713/AJS.V50I1.994","url":null,"abstract":"It is known that data such as business sales and household income need data transformation prior to regression estimate as the data has a homoscedastic error. However, data transformations make the estimation of mean and total unstable. Therefore, the ratio model is often used for imputation in the field of official statistics to avoid the problem. Our study aims to robustify the estimator following the ratio model by means of Mestimation. Reformulation of the conventional ratio model with homoscedastic quasi-error term provides quasi-residuals which can be used as a measure of outlyingness as same as a linear regression model. A generalisation of the model, which accommodates varied error terms with different heteroscedasticity, is also proposed. Functions for robustified estimators of the generalised ratio model are implemented by the iterative re-weighted least squares algorithm in R environment and illustrated using random datasets. Monte Carlo simulation confirms accuracy of the proposed estimators, as well as their computational efficiency. A comparison of the scale parameters between the average absolute deviation (AAD) and median absolute deviation (MAD) is made regarding Tukey’s biweight function. The results with Huber’s weight function are also provided for reference. The proposed robust estimator of the generalised ratio model is used for imputation of major corporate accounting items of the 2016 Economic Census for Business Activity in Japan.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"120 1","pages":"74-87"},"PeriodicalIF":0.6,"publicationDate":"2021-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87959545","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

Impact of Covariates in Compositional Models and Simplicial Derivatives 组合模型和单纯导数中协变量的影响

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Austrian Journal of Statistics Pub Date : 2021-02-03 DOI: 10.17713/AJS.V50I2.1069

Joanna Morais, C. Thomas-Agnan

{"title":"Impact of Covariates in Compositional Models and Simplicial Derivatives","authors":"Joanna Morais, C. Thomas-Agnan","doi":"10.17713/AJS.V50I2.1069","DOIUrl":"https://doi.org/10.17713/AJS.V50I2.1069","url":null,"abstract":"In the framework of Compositional Data Analysis, vectors carrying relative information, also called compositional vectors, can appear in regression models either as dependent or as explanatory variables. In some situations, they can be on both sides of the regression equation. Measuring the marginal impacts of covariates in these types of models is not straightforward since a change in one component of a closed composition automatically affects the rest of the composition. Previous work by the authors has shown how to measure, compute and interpret these marginal impacts in the case of linear regression models with compositions on both sides of the equation. The resulting natural interpretation is in terms of an elasticity, a quantity commonly used in econometrics and marketing applications. They also demonstrate the link between these elasticities and simplicial derivatives. The aim of this contribution is to extend these results to other situations, namely when the compositional vector is on a single side of the regression equation. In these cases, the marginal impact is related to a semi-elasticity and also linked to some simplicial derivative. Moreover we consider the possibility that a total variable is used as an explanatory variable, with several possible interpretations of this total and we derive the elasticity formulas in that case.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"16 1","pages":"1-15"},"PeriodicalIF":0.6,"publicationDate":"2021-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85019286","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

A Bibliometric Analysis of the 35th anniversary of the paper "The Statistical Analysis of Compositional Data" by John Aitchison (1982) 约翰·艾奇逊(1982)论文《成分数据的统计分析》发表35周年文献计量学分析

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Austrian Journal of Statistics Pub Date : 2021-02-03 DOI: 10.17713/AJS.V50I2.1066

C. Navarro, Silvia González-Morcillo, Carles Mulet-Forteza, Salvador Linares-Mustarós

{"title":"A Bibliometric Analysis of the 35th anniversary of the paper \"The Statistical Analysis of Compositional Data\" by John Aitchison (1982)","authors":"C. Navarro, Silvia González-Morcillo, Carles Mulet-Forteza, Salvador Linares-Mustarós","doi":"10.17713/AJS.V50I2.1066","DOIUrl":"https://doi.org/10.17713/AJS.V50I2.1066","url":null,"abstract":"This study presents a comprehensive bibliometric analysis of the paper published by John Aitchison in the Journal of the Royal Statistical Society. Series B (Methodological) in 1982. Having recently reached the milestone of 35 years since its publication, this pioneering paper was the first to illustrate the use of the methodology \"Compositional Data Analysis\" or \"CoDA\". By October 2019, this paper had received over 780 citations, making it the most widely cited and influential article among those using said methodology. The bibliometric approach used in this study encompasses a wide range of techniques, including a specific analysis of the main authors and institutions to have cited Aitchison' paper. The VOSviewer software was also used for the purpose of developing network maps for said publication. Specifically, the techniques used were co-citations and bibliographic coupling. The results clearly show the significant impact the paper has had on scientific research, having been cited by authors and institutions that publish all around the world.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"81 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76632131","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

Likelihood Ratio Test and Non-parametric Test for Load Sharing 负荷分担的似然比检验和非参数检验

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Austrian Journal of Statistics Pub Date : 2021-02-01 DOI: 10.17713/AJS.V50I1.979

S. Sutar

引用次数: 0

Construction of Windows for Pharmacokinetic Sampling 药代动力学取样窗口的构建

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Austrian Journal of Statistics Pub Date : 2021-01-01 DOI: 10.17713/ajs.v50i5.1110

M. Alam, Nigar Sultana

{"title":"Construction of Windows for Pharmacokinetic Sampling","authors":"M. Alam, Nigar Sultana","doi":"10.17713/ajs.v50i5.1110","DOIUrl":"https://doi.org/10.17713/ajs.v50i5.1110","url":null,"abstract":"This paper describes a method for the construction of pharmacokinetic sampling windows so that they are around the $D$-optimum time points. Here we consider the situation where a pharmacokinetic (PK) study is accompanied by a dose-finding study in phase I clinical trial. The D-optimal criterion is often used to determine the optimal time for collecting blood samples so that they provide maximum information regarding the population PK parameters. However, collecting blood samples at the D-optimal time points is often difficult. Instead, the sampling time point chosen from a suitable time interval or window can ease the process. The proposed method is conceptually simple and considers the average value and standard deviation of D-optimal time points up to create sampling windows. Random time points can be chosen from these windows then to collect blood samples from the next cohort. The nonlinear random-effects model has been used to model the PK data. Also, we employ the continual reassessment method for dose allocation to the patients. Comparisons of the accuracy and precision for the PK parameter estimates obtained at the D-optimal and random time points are also presented. The results are convincing enough to suggest the proposed method as a useful tool for blood sample collection.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"62 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84910552","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

Estimation of the Inverse Weibull Distribution Parameters under Type-I Hybrid Censoring i型混合滤波下逆威布尔分布参数的估计

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Austrian Journal of Statistics Pub Date : 2021-01-01 DOI: 10.17713/ajs.v50i5.1134

Mohammad Kazemi, Mina Azizpoor

引用次数: 2

Generalized Topp-Leone-Weibull AFT Modelling: A Bayesian Analysis with MCMC Tools using R and Stan 广义Topp-Leone-Weibull AFT建模:基于R和Stan的MCMC工具的贝叶斯分析

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Austrian Journal of Statistics Pub Date : 2021-01-01 DOI: 10.17713/ajs.v50i5.1166

Md. Ashraf-Ul-Alam, A. A. Khan

引用次数: 8

A Bivariate Index Vector to Measure Departure from Quasi-symmetry for Ordinal Square Contingency Tables 一个度量序平方列联表偏离拟对称的二元指标向量

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Austrian Journal of Statistics Pub Date : 2021-01-01 DOI: 10.17713/ajs.v50i5.1206

S. Ando

{"title":"A Bivariate Index Vector to Measure Departure from Quasi-symmetry for Ordinal Square Contingency Tables","authors":"S. Ando","doi":"10.17713/ajs.v50i5.1206","DOIUrl":"https://doi.org/10.17713/ajs.v50i5.1206","url":null,"abstract":"This study proposes a bivariate index vector to concurrently analyze both the degree and direction of departure from the quasi-symmetry (QS) model for ordinal square contingency tables. The QS model and extended QS (EQS) models identify the symmetry and asymmetry between the probabilities of normal circulation and reverse circulation when the order exists for arbitrary three categories. The asymmetry parameter of the EQS model implies the degree of departure from the QS model; the EQS model is equivalent to the QS model when the asymmetry parameter equals to one. The structure of the EQS model differs depending on whether the asymmetry parameter approaches zero or infinity. Thus, the asymmetry parameter of the EQS model also implies the direction of departure from the QS model. The proposed bivariate index vector is constructed by combining existing and original sub-indexes that represent the degree of departure from the QS model and its direction. These sub-indexes are expressed as functions of the asymmetry parameter under the EQS model. We construct an estimator of the proposed bivariate index vector and an approximate confidence region for the proposed bivariate index vector. Using real data, we show that the proposed bivariate index vector is important to compare degrees of departure from the QS model for plural data sets.","PeriodicalId":51761,"journal":{"name":"Austrian Journal of Statistics","volume":"24 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79464602","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