Journal of the royal statistical society series b-methodological最新文献_第3页

Multivariate Mean Parameter Estimation by Using a Partly Exponential Model 基于部分指数模型的多元均值参数估计

Journal of the royal statistical society series b-methodological Pub Date : 1992-07-01 DOI: 10.1111/J.2517-6161.1992.TB01453.X

L. Zhao, R. Prentice, S. Self

引用次数: 107

Identifying Multiple Outliers in Multivariate Data 识别多变量数据中的多个异常值

Journal of the royal statistical society series b-methodological Pub Date : 1992-07-01 DOI: 10.1111/J.2517-6161.1992.TB01449.X

A. Hadi

{"title":"Identifying Multiple Outliers in Multivariate Data","authors":"A. Hadi","doi":"10.1111/J.2517-6161.1992.TB01449.X","DOIUrl":"https://doi.org/10.1111/J.2517-6161.1992.TB01449.X","url":null,"abstract":"SUMMARY We propose a procedure for the detection of multiple outliers in multivariate data. Let Xbe an n x p data matrix representing n observations onp variates. We first order the n observations, using an appropriately chosen robust measure of outlyingness, then divide the data set into two initial subsets: a 'basic' subset which containsp + 1 'good' observations and a 'nonbasic' subset which contains the remaining n -p - 1 observations. Second, we compute the relative distance from each point in the data set to the centre of the basic subset, relative to the (possibly singular) covariance matrix of the basic subset. Third, we rearrange the n observations in ascending order accordingly, then divide the data set into two subsets: a basic subset which contains the first p +2 observations and a non-basic subset which contains the remaining n -p -2 observations. This process is repeated until an appropriately chosen stopping criterion is met. The final non-basic subset of observations is declared an outlying subset. The procedure proposed is illustrated and compared with existing methods by using several data sets. The procedure is simple, computationally inexpensive, suitable for automation, computable with widely available software packages, effective in dealing with masking and swamping problems and, most importantly, successful in identifying multivariate outliers.","PeriodicalId":17425,"journal":{"name":"Journal of the royal statistical society series b-methodological","volume":"45 1","pages":"761-771"},"PeriodicalIF":0.0,"publicationDate":"1992-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88100585","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: 816

Confidence sets having the shape of a half-space 具有半空间形状的置信度集

Journal of the royal statistical society series b-methodological Pub Date : 1992-07-01 DOI: 10.1111/J.2517-6161.1992.TB01456.X

François Perron

引用次数: 0

Exact and Approximate Posterior Moments for a Normal Location Parameter 正常位置参数的精确和近似后验矩

Journal of the royal statistical society series b-methodological Pub Date : 1992-07-01 DOI: 10.1111/J.2517-6161.1992.TB01452.X

L. Pericchi, Adrian F. M. Smith

引用次数: 82

A Goodness‐Of‐Fit Test for Time Series with Long Range Dependence 具有长期相关性的时间序列的拟合优度检验

Journal of the royal statistical society series b-methodological Pub Date : 1992-07-01 DOI: 10.1111/J.2517-6161.1992.TB01448.X

J. Beran

引用次数: 89

A New Method of Prediction for Spatial Regression Models with Correlated Errors 具有相关误差的空间回归模型预测新方法

Journal of the royal statistical society series b-methodological Pub Date : 1992-07-01 DOI: 10.1111/J.2517-6161.1992.TB01454.X

A. V. Vecchia

引用次数: 25

Testing exponentiality based on Kullback-Leibler information 基于Kullback-Leibler信息的指数性检验

Journal of the royal statistical society series b-methodological Pub Date : 1992-07-01 DOI: 10.1111/J.2517-6161.1992.TB01447.X

N. Ebrahimi, M. Habibullah, E. Soofi

引用次数: 183

Diagnostics in categorical data analysis 分类数据分析中的诊断

Journal of the royal statistical society series b-methodological Pub Date : 1992-07-01 DOI: 10.1111/J.2517-6161.1992.TB01451.X

E. Andersen

引用次数: 37

On Use of the EM Algorithm for Penalized Likelihood Estimation EM算法在惩罚似然估计中的应用

Journal of the royal statistical society series b-methodological Pub Date : 1990-07-01 DOI: 10.1111/J.2517-6161.1990.TB01798.X

P. Green

{"title":"On Use of the EM Algorithm for Penalized Likelihood Estimation","authors":"P. Green","doi":"10.1111/J.2517-6161.1990.TB01798.X","DOIUrl":"https://doi.org/10.1111/J.2517-6161.1990.TB01798.X","url":null,"abstract":"SUMMARY The EM algorithm is a popular approach to maximum likelihood estimation but has not been much used for penalized likelihood or maximum a posteriori estimation. This paper discusses properties of the EM algorithm in such contexts, concentrating on rates of conver- gence, and presents an alternative that is usually more practical and converges at least as quickly. The EM algorithm is a general approach to maximum likelihood estimation, rather than a specific algorithm. Dempster et al. (1977) discussed the method and derived basic properties, demonstrating that a variety of procedures previously developed rather informally could be unified. The common strand to problems where the approach is applicable is a notion of 'incomplete data'; this includes the conventional sense of 'missing data' but is much broader than that. The EM algorithm demon- strates its strength in situations where some hypothetical experiment yields data from which estimation is particularly convenient and economical: the 'incomplete' data actually at hand are regarded as observable functions of these 'complete' data. The resulting algorithms, while usually slow to converge, are often extremely simple and remain practical in large problems where no other approaches may be feasible. Dempster et al. (1977) briefly refer to the use of the same approach to the problem of finding the posterior mode (maximum a posteriori estimate) in a Bayesian estima-","PeriodicalId":17425,"journal":{"name":"Journal of the royal statistical society series b-methodological","volume":"80 1","pages":"443-452"},"PeriodicalIF":0.0,"publicationDate":"1990-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87336707","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: 393

Estimation and Inference by Compact Coding 基于压缩编码的估计与推理

Journal of the royal statistical society series b-methodological Pub Date : 1987-07-01 DOI: 10.1111/J.2517-6161.1987.TB01695.X

C. S. Wallace, P. Freeman

引用次数: 586