Australian & New Zealand Journal of Statistics最新文献_第7页

Modelling students’ career indicators via mixtures of parsimonious matrix-normal distributions 通过简洁矩阵-正态分布的混合模型对学生的职业指标进行建模

IF 1.1 4区数学

Australian & New Zealand Journal of Statistics Pub Date : 2022-02-10 DOI: 10.1111/anzs.12351

Salvatore D. Tomarchio, Salvatore Ingrassia, Volodymyr Melnykov

引用次数: 2

Spying on the prior of the number of data clusters and the partition distribution in Bayesian cluster analysis 监视贝叶斯聚类分析中数据簇数的先验性和分区分布

IF 1.1 4区数学

Australian & New Zealand Journal of Statistics Pub Date : 2022-02-10 DOI: 10.1111/anzs.12350

Jan Greve, Bettina Grün, Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter

{"title":"Spying on the prior of the number of data clusters and the partition distribution in Bayesian cluster analysis","authors":"Jan Greve, Bettina Grün, Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter","doi":"10.1111/anzs.12350","DOIUrl":"10.1111/anzs.12350","url":null,"abstract":"<p>Cluster analysis aims at partitioning data into groups or clusters. In applications, it is common to deal with problems where the number of clusters is unknown. Bayesian mixture models employed in such applications usually specify a flexible prior that takes into account the uncertainty with respect to the number of clusters. However, a major empirical challenge involving the use of these models is in the characterisation of the induced prior on the partitions. This work introduces an approach to compute descriptive statistics of the prior on the partitions for three selected Bayesian mixture models developed in the areas of Bayesian finite mixtures and Bayesian nonparametrics. The proposed methodology involves computationally efficient enumeration of the prior on the number of clusters in-sample (termed as ‘data clusters’) and determining the first two prior moments of symmetric additive statistics characterising the partitions. The accompanying reference implementation is made available in the <span>R</span> package <span>fipp</span>. Finally, we illustrate the proposed methodology through comparisons and also discuss the implications for prior elicitation in applications.</p>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"64 2","pages":"205-229"},"PeriodicalIF":1.1,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/anzs.12350","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72830218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 11

Variable selection and debiased estimation for single-index expectile model 单指标期望模型的变量选择与去偏估计

IF 1.1 4区数学

Australian & New Zealand Journal of Statistics Pub Date : 2022-02-02 DOI: 10.1111/anzs.12348

Rong Jiang, Yexun Peng, Yufei Deng

引用次数: 0

Efficient estimation of partially linear tail index models using B-splines 部分线性尾指数模型的b样条有效估计

IF 1.1 4区数学

Australian & New Zealand Journal of Statistics Pub Date : 2022-02-02 DOI: 10.1111/anzs.12357

Yaolan Ma, Bo Wei

引用次数: 0

Properties of the affine-invariant ensemble sampler's ‘stretch move’ in high dimensions 高维仿射不变系综采样器“拉伸移动”的性质

IF 1.1 4区数学

Australian & New Zealand Journal of Statistics Pub Date : 2022-02-02 DOI: 10.1111/anzs.12358

David Huijser, Jesse Goodman, Brendon J. Brewer

{"title":"Properties of the affine-invariant ensemble sampler's ‘stretch move’ in high dimensions","authors":"David Huijser, Jesse Goodman, Brendon J. Brewer","doi":"10.1111/anzs.12358","DOIUrl":"10.1111/anzs.12358","url":null,"abstract":"<div>\u0000 \u0000 <p>We present theoretical and practical properties of the affine-invariant ensemble sampler Markov Chain Monte Carlo method. In high dimensions, the sampler's ‘stretch move’ has unusual and undesirable properties. We demonstrate this with an <i>n</i>-dimensional correlated Gaussian toy problem with a known mean and covariance structure, and a multivariate version of the Rosenbrock problem. Visual inspection of a trace plots suggests the burn-in period is short. Upon closer inspection, we discover the mean and the variance of the target distribution do not match the known values, and the chain takes a very long time to converge. This problem becomes severe as <i>n</i> increases beyond 50. We also applied different diagnostics adapted to be applicable to ensemble methods to determine any lack of convergence. The diagnostics include the Gelman–Rubin method, the Heidelberger–Welch test, the integrated autocorrelation and the acceptance rate. The trace plot of individual walkers appears to be useful as well. We therefore conclude that the stretch move should be used with caution in moderate to high dimensions. We also present some heuristic results explaining this behaviour.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"64 1","pages":"1-26"},"PeriodicalIF":1.1,"publicationDate":"2022-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88726225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 6

Global implicit function theorems and the online expectation–maximisation algorithm 全局隐函数定理和在线期望最大化算法

IF 1.1 4区数学

Australian & New Zealand Journal of Statistics Pub Date : 2022-01-24 DOI: 10.1111/anzs.12356

Hien Duy Nguyen, Florence Forbes

{"title":"Global implicit function theorems and the online expectation–maximisation algorithm","authors":"Hien Duy Nguyen, Florence Forbes","doi":"10.1111/anzs.12356","DOIUrl":"10.1111/anzs.12356","url":null,"abstract":"The expectation–maximisation (EM) algorithm framework is an important tool for statistical computation. Due to the changing nature of data, online and mini‐batch variants of EM and EM‐like algorithms have become increasingly popular. The consistency of the estimator sequences that are produced by these EM variants often rely on an assumption regarding the continuous differentiability of a parameter update function. In many cases, the parameter update function is not in closed form and may only be defined implicitly, which makes the verification of the continuous differentiability property difficult. We demonstrate how a global implicit function theorem can be used to verify such properties in the cases of finite mixtures of distributions in the exponential family, and more generally, when the component‐specific distributions admit data augmentation schemes, within the exponential family. We then illustrate the use of such a theorem in the cases of mixtures of beta distributions, gamma distributions, fully visible Boltzmann machines and Student distributions. Via numerical simulations, we provide empirical evidence towards the consistency of the online EM algorithm parameter estimates in such cases.","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"64 2","pages":"255-281"},"PeriodicalIF":1.1,"publicationDate":"2022-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83582209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 5

Sufficient dimension reduction for clustered data via finite mixture modelling 通过有限混合模型对聚类数据进行足够的降维

IF 1.1 4区数学

Australian & New Zealand Journal of Statistics Pub Date : 2022-01-22 DOI: 10.1111/anzs.12349

F.K.C. Hui, L.H. Nghiem

{"title":"Sufficient dimension reduction for clustered data via finite mixture modelling","authors":"F.K.C. Hui, L.H. Nghiem","doi":"10.1111/anzs.12349","DOIUrl":"10.1111/anzs.12349","url":null,"abstract":"<div>\u0000 \u0000 <p>Sufficient dimension reduction (SDR) is an attractive approach to regression modelling. However, despite its rich literature and growing popularity in application, surprisingly little research has been done on how to perform SDR for clustered data, for example as is commonly arises in longitudinal studies. Indeed, current popular SDR methods have been mostly based on a marginal estimating equation approach. In this article, we propose a new approach to SDR for clustered data based on a combination of finite mixture modelling and mixed effects regression. Finite mixture models offer a flexible means of estimating the fixed effects central subspace, based on slicing the space up and probabilistically clustering observations to each slice (mixture component). Dimension reduction is achieved by having the mixing proportions vary only through the sufficient fixed effect predictors. We then incorporate random effects as a natural means of accounting for correlations within clusters. We employ a Monte Carlo expectation–maximisation algorithm to estimate the model parameters and fixed effects central subspace, and discuss methods for associated uncertainty quantification and prediction. Simulation studies demonstrate that our approach performs strongly against both estimating equation methods for estimating the fixed effects central subspace, and SDR methods which do not account for within-cluster correlation. Finally, we apply the proposed approach to a data set on air pollutant monitoring across 13 stations in the Eastern United States.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"64 2","pages":"133-157"},"PeriodicalIF":1.1,"publicationDate":"2022-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73971724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 2

Bayesian credible intervals for population attributable risk from case–control, cohort and cross-sectional studies 来自病例对照、队列和横断面研究的人群归因风险的贝叶斯可信区间

IF 1.1 4区数学

Australian & New Zealand Journal of Statistics Pub Date : 2022-01-17 DOI: 10.1111/anzs.12352

Sarah Pirikahu, Geoffrey Jones, Martin L. Hazelton

{"title":"Bayesian credible intervals for population attributable risk from case–control, cohort and cross-sectional studies","authors":"Sarah Pirikahu, Geoffrey Jones, Martin L. Hazelton","doi":"10.1111/anzs.12352","DOIUrl":"10.1111/anzs.12352","url":null,"abstract":"<div>\u0000 \u0000 <p>Population attributable risk (PAR) and population attributable fraction (PAF) are used in epidemiology to predict the impact of removing a risk factor from the population. Until recently, no standard approach for calculating confidence intervals or the variance for PAR in particular was available in the literature. Previously we outlined a fully Bayesian approach to provide credible intervals for the PAR and PAF from a cross-sectional study, where the data was presented in the form of a 2×2 table. However, extensions to cater for other frequently used study designs were not provided. In this paper we provide methodology to calculate credible intervals for the PAR and PAF for case–control and cohort studies. Additionally, we extend the cross-sectional example to allow for the incorporation of uncertainty that arises when an imperfect diagnostic test is used. In all these situations the model becomes over-parameterised, or non-identifiable, which can result in standard ‘off-the-shelf’ Markov Chain Monte Carlo (MCMC) updaters taking a long time to converge or even failing altogether. We adapt an importance sampling methodology to overcome this problem, and propose some novel MCMC samplers that take into consideration the shape of the posterior ridge to aid in the convergence of the Markov chain.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"63 4","pages":"639-657"},"PeriodicalIF":1.1,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79829223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Measuring the values of cricket players 衡量板球运动员的价值

IF 1.1 4区数学

Australian & New Zealand Journal of Statistics Pub Date : 2022-01-15 DOI: 10.1111/anzs.12353

Pranjal Chandrakar, Shubhabrata Das

{"title":"Measuring the values of cricket players","authors":"Pranjal Chandrakar, Shubhabrata Das","doi":"10.1111/anzs.12353","DOIUrl":"10.1111/anzs.12353","url":null,"abstract":"<div>\u0000 \u0000 <p>Sports franchises that participate in team sports can make better decisions regarding their players’ financial compensation, renewal of the contracts, bidding strategies during the auction, etc., if they can adequately assess the value or worth of their players. Evaluating the value of a player in a team sport is difficult because various team members play different roles. In this study, we resolve this by measuring the value of a player in terms of how his inclusion in the team affects the team's probability of winning. With this notion of value, we develop a technique to measure the worth of a cricket player for his franchise. To illustrate this technique, we evaluate the values of cricket players who play in the Indian Premier League. We also study the relationship between players’ values and their salaries. We find that a few popular players earn disproportionately more than others. This disproportionality in the income of popular players cannot be justified by their performance alone, as adjudged by their values in this work. We attribute the disproportionality in the income to the factors not captured via conventional yardsticks, including leadership or brand value.</p>\u0000 </div>","PeriodicalId":55428,"journal":{"name":"Australian & New Zealand Journal of Statistics","volume":"63 4","pages":"565-578"},"PeriodicalIF":1.1,"publicationDate":"2022-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74128017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Detection boundary for a sparse gamma scale mixture model 稀疏伽玛尺度混合模型的检测边界

IF 1.1 4区数学

Australian & New Zealand Journal of Statistics Pub Date : 2022-01-11 DOI: 10.1111/anzs.12347

Michael I. Stewart

引用次数: 1