International Statistical Review最新文献_第3页

An Optimised Optional Randomised Response Technique 优化的可选随机应变技术

IF 2 3区数学

International Statistical Review Pub Date : 2024-05-29 DOI: 10.1111/insr.12581

Kavya Pushadapu, Sarjinder Singh, Stephen A. Sedory

引用次数: 0

Joint Robust Variable Selection of Mean and Covariance Model via Shrinkage Methods 通过缩减法对均值和协方差模型进行联合稳健变量选择

IF 2 3区数学

International Statistical Review Pub Date : 2024-05-24 DOI: 10.1111/insr.12577

Y. Güney, Fulya Gokalp Yavuz, Olcay Arslan

{"title":"Joint Robust Variable Selection of Mean and Covariance Model via Shrinkage Methods","authors":"Y. Güney, Fulya Gokalp Yavuz, Olcay Arslan","doi":"10.1111/insr.12577","DOIUrl":"https://doi.org/10.1111/insr.12577","url":null,"abstract":"A valuable and robust extension of the traditional joint mean and the covariance models when data subject to outliers and/or heavy‐tailed outcomes can be achieved using the joint modelling of location and scatter matrix of the multivariate t‐distribution. This model encompasses three models in itself, and the number of unknown parameters in the covariance model increases quadratically with the matrix size. As a result, selecting the important variables becomes a crucial aspect to consider. In this context, the variable selection combined with the parameter estimation is considered under the normality assumption. However, because of the non‐robustness of the normal distribution, the resulting estimators will be sensitive to outliers and/or heavy taildness in the data. This paper has two objectives to overcome these problems. The first is to obtain the maximum likelihood estimates of the parameters and propose an expectation‐maximisation type algorithm as an alternative to the Fisher scoring algorithm in the literature. We also consider simultaneous parameter estimation and variable selection in the multivariate t‐joint location and scatter matrix models. The consistency and oracle properties of the regularised estimators are also established. Simulation studies and real data analysis are provided to assess the performance of the proposed methods.","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141099030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Survey of Monte Carlo Methods for Noisy and Costly Densities With Application to Reinforcement Learning and ABC 噪声和高成本密度的蒙特卡洛方法概览--应用于强化学习和 ABC

IF 2 3区数学

International Statistical Review Pub Date : 2024-05-17 DOI: 10.1111/insr.12573

Fernando Llorente, Luca Martino, Jesse Read, David Delgado‐Gómez

引用次数: 0

ODC and ROC Curves, Comparison Curves and Stochastic Dominance ODC 和 ROC 曲线、比较曲线和随机优势†。

IF 1.7 3区数学

International Statistical Review Pub Date : 2024-05-08 DOI: 10.1111/insr.12571

Teresa Ledwina, Adam Zagdański

{"title":"ODC and ROC Curves, Comparison Curves and Stochastic Dominance","authors":"Teresa Ledwina, Adam Zagdański","doi":"10.1111/insr.12571","DOIUrl":"10.1111/insr.12571","url":null,"abstract":"<div>\u0000 \u0000 <p>We discuss two novel approaches to inter-distributional comparisons in the classical two-sample problem. Our starting point is properly standardised and combined, very popular in several areas of statistics and data analysis, ordinal dominance and receiver characteristic curves, denoted by ODC and ROC, respectively. The proposed new curves are termed the comparison curves. Their estimates, being weighted rank processes on (0,1), form the basis of inference. These weighted processes are intuitive, well-suited for visual inspection of data at hand and are also useful for constructing some formal inferential procedures. They can be applied to several variants of two-sample problem. Their use can help improve some existing procedures both in terms of power and the ability to identify the sources of departures from the postulated model. To simplify interpretation of finite sample results, we restrict attention to values of the processes on a finite grid of points. This results in the so-called bar plots (B-plots), which readably summarise the information contained in the data. What is more, we show that B-plots along with adjusted simultaneous acceptance regions provide principled information about where the model departs from the data. This leads to a framework that facilitates identification of regions with locally significant differences.</p>\u0000 <p>We show an implementation of the considered techniques to a standard stochastic dominance testing problem. Some min-type statistics are introduced and investigated. A simulation study compares two tests pertinent to the comparison curves to well-established tests in the literature and demonstrates the strong and competitive performance of the former in many typical situations. Some real data applications illustrate simplicity and practical usefulness of the proposed approaches. A range of other applications of considered weighted processes is briefly discussed too.</p>\u0000 </div>","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140938951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Raise Regression: Justification, Properties and Application 提升回归：理由、特性和应用

IF 2 3区数学

International Statistical Review Pub Date : 2024-05-02 DOI: 10.1111/insr.12575

Román Salmerón‐Gómez, Catalina B. García‐García, José García‐Pérez

{"title":"The Raise Regression: Justification, Properties and Application","authors":"Román Salmerón‐Gómez, Catalina B. García‐García, José García‐Pérez","doi":"10.1111/insr.12575","DOIUrl":"https://doi.org/10.1111/insr.12575","url":null,"abstract":"SummaryMulticollinearity results in inflation in the variance of the ordinary least squares estimators due to the correlation between two or more independent variables (including the constant term). A widely applied solution is to estimate with penalised estimators such as the ridge estimator, which trade off some bias in the estimators to gain a reduction in the variance of these estimators. Although the variance diminishes with these procedures, all seem to indicate that the inference and goodness of fit are controversial. Alternatively, the raise regression allows mitigation of the problems associated with multicollinearity without the loss of inference or the coefficient of determination. This paper completely formalises the raise estimator. For the first time, the norm of the estimator, the behaviour of the individual and joint significance, the behaviour of the mean squared error and the coefficient of variation are analysed. We also present the generalisation of the estimation and the relation between the raise and the residualisation estimators. To have a better understanding of raise regression, previous contributions are also summarised: its mean squared error, the variance inflation factor, the condition number, adequate selection of the variable to be raised, the successive raising, and the relation between the raise and the ridge estimator. The usefulness of the raise regression as an alternative to mitigate multicollinearity is illustrated with two empirical applications.","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140837225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

One-Inflation and Zero-Truncation Count Data Modelling Revisited With a View on Horvitz–Thompson Estimation of Population Size 以 Horvitz-Thompson 人口规模估算为视角，重新审视单膨胀和零截断计数数据建模法

IF 1.7 3区数学

International Statistical Review Pub Date : 2024-04-30 DOI: 10.1111/insr.12570

Dankmar Böhning, Herwig Friedl

{"title":"One-Inflation and Zero-Truncation Count Data Modelling Revisited With a View on Horvitz–Thompson Estimation of Population Size","authors":"Dankmar Böhning, Herwig Friedl","doi":"10.1111/insr.12570","DOIUrl":"10.1111/insr.12570","url":null,"abstract":"<p>Estimating the size of a hard-to-count population is a challenging matter. We consider uni-list approaches in which the count of identifications per unit is the basis of analysis. Unseen units have a zero count and do not occur in the sample leading to a zero-truncated setting. Because of various mechanisms, one-inflation is often an occurring phenomena that can lead to seriously biased estimates of population size. The current work reviews some recent advances on one-inflation and zero-truncation modelling, and furthermore focuses here on the impact it has on population size estimation. The zero-truncated one-inflated and the one-inflated zero-truncated model is compared (also with the model ignoring one-inflation) in terms of Horvitz–Thompson estimation of population size. The simulation work shows clearly the biasing effect of ignoring one-inflation. Both models, the zero-truncated one-inflated and the one-inflated zero-truncated one, are suitable to model ongoing one-inflation. It is also important to choose an appropriate base-line distributional model. Finally, all models derived in the paper are illustrated on a number of case studies.</p>","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/insr.12570","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140837218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Small Sample Inference for Two‐Way Capture‐Recapture Experiments 双向捕获-再捕获实验的小样本推断

IF 2 3区数学

International Statistical Review Pub Date : 2024-04-24 DOI: 10.1111/insr.12574

Louis‐Paul Rivest, Mamadou Yauck

{"title":"Small Sample Inference for Two‐Way Capture‐Recapture Experiments","authors":"Louis‐Paul Rivest, Mamadou Yauck","doi":"10.1111/insr.12574","DOIUrl":"https://doi.org/10.1111/insr.12574","url":null,"abstract":"SummaryThe properties of the generalised Waring distribution defined on the non‐negative integers are reviewed. Formulas for its moments and its mode are given. A construction as a mixture of negative binomial distributions is also presented. Then we turn to the Petersen model for estimating the population size in a two‐way capture‐recapture experiment. We construct a Bayesian model for by combining a Waring prior with the hypergeometric distribution for the number of units caught twice in the experiment. Credible intervals for are obtained using quantiles of the posterior, a generalised Waring distribution. The standard confidence interval for the population size constructed using the asymptotic variance of Petersen estimator and 0.5 logit transformed interval are shown to be special cases of the generalised Waring credible interval. The true coverage of this interval is shown to be bigger than or equal to its nominal converage in small populations, regardless of the capture probabilities. In addition, its length is substantially smaller than that of the 0.5 logit transformed interval. Thus, the proposed generalised Waring credible interval appears to be the best way to quantify the uncertainty of the Petersen estimator for populations size.","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140798380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nonresponse Bias Analysis in Longitudinal Studies: A Comparative Review with an Application to the Early Childhood Longitudinal Study 纵向研究中的无应答偏差分析：应用于幼儿纵向研究的比较综述

IF 1.7 3区数学

International Statistical Review Pub Date : 2024-03-19 DOI: 10.1111/insr.12566

Yajuan Si, Roderick J.A. Little, Ya Mo, Nell Sedransk

{"title":"Nonresponse Bias Analysis in Longitudinal Studies: A Comparative Review with an Application to the Early Childhood Longitudinal Study","authors":"Yajuan Si, Roderick J.A. Little, Ya Mo, Nell Sedransk","doi":"10.1111/insr.12566","DOIUrl":"10.1111/insr.12566","url":null,"abstract":"<p>Longitudinal studies are subject to nonresponse when individuals fail to provide data for entire waves or particular questions of the survey. We compare approaches to nonresponse bias analysis (NRBA) in longitudinal studies and illustrate them on the Early Childhood Longitudinal Study, Kindergarten Class of 2010–2011 (ECLS-K:2011). Wave nonresponse with attrition often yields a monotone missingness pattern, and the missingness mechanism can be missing at random (MAR) or missing not at random (MNAR). We discuss weighting, multiple imputation (MI), incomplete data modelling and Bayesian approaches to NRBA for monotone patterns. Weighting adjustments can be effective when the constructed weights are correlated with the survey outcome of interest. MI allows for variables with missing values to be included in the imputation model, yielding potentially less biased and more efficient estimates. We add offsets in the MAR results to provide sensitivity analyses to assess MNAR deviations. We conduct NRBA for descriptive summaries and analytic model estimates in the ECLS-K:2011 application. The strength of evidence about our NRBA depends on the strength of the relationship between the fully observed variables and the key survey outcomes, so the key to a successful NRBA is to include strong predictors.</p>","PeriodicalId":14479,"journal":{"name":"International Statistical Review","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/insr.12566","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140169849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multidimensional Stationary Time Series Dimension Reduction and Prediction Marianna Bolla, Tamás SzabadosRoutledge, 2023, xiv + 318 pages, $59.95, paperback ISBN: 9780367619701 多维静态时间序列降维与预测MariannaBolla，TamásSzabadosRoutledge，2023，xiv + 318页，59.95美元，平装 ISBN：9780367619701

IF 2 3区数学

International Statistical Review Pub Date : 2024-03-12 DOI: 10.1111/insr.12567

Brian W. Sloboda

引用次数: 0

A Slicing-Free Perspective to Sufficient Dimension Reduction: Selective Review and Recent Developments 充分降维的无切片视角：选择性回顾与最新发展

IF 1.7 3区数学

International Statistical Review Pub Date : 2024-03-07 DOI: 10.1111/insr.12565

Lu Li, Xiaofeng Shao, Zhou Yu

引用次数: 0