Journal of the Royal Statistical Society. Series B: Statistical Methodology

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Sparse Additive Models
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 71 Số 5 - Trang 1009-1030 - 2009
Pradeep Ravikumar, John Lafferty, Han Liu, Larry Wasserman
SummaryWe present a new class of methods for high dimensional non-parametric regression and classification called sparse additive models. Our methods combine ideas from sparse linear modelling and additive non-parametric regression. We derive an algorithm for fitting the models that is practical and effective even when the number of covariates is larger than the sa...... hiện toàn bộ
Probabilistic Principal Component Analysis
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 61 Số 3 - Trang 611-622 - 1999
Michael E. Tipping, Chris Bishop
Summary Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based on a probability model. We demonstrate how the principal axes of a set of observed data vectors may be determined through maximum likelihood estimation of parameters in a latent variable model that is closely related to fa...... hiện toàn bộ
Soap Film Smoothing
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 70 Số 5 - Trang 931-955 - 2008
Simon N. Wood, Mark V. Bravington, Sharon L. Hedley
SummaryConventional smoothing methods sometimes perform badly when used to smooth data over complex domains, by smoothing inappropriately across boundary features, such as peninsulas. Solutions to this smoothing problem tend to be computationally complex, and not to provide model smooth functions which are appropriate for incorporating as components of other models...... hiện toàn bộ
Generalized Linear Array Models with Applications to Multidimensional Smoothing
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 68 Số 2 - Trang 259-280 - 2006
Iain D. Currie, Maŕıa Durbán, Paul H.C. Eilers
SummaryData with an array structure are common in statistics, and the design or regression matrix for analysis of such data can often be written as a Kronecker product. Factorial designs, contingency tables and smoothing of data on multidimensional grids are three such general classes of data and models. In such a setting, we develop an arithmetic of arrays which a...... hiện toàn bộ
Spatiotemporal Prediction for Log-Gaussian Cox Processes
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 63 Số 4 - Trang 823-841 - 2001
Anders Brix, Peter J. Diggle
Summary Space–time point pattern data have become more widely available as a result of technological developments in areas such as geographic information systems. We describe a flexible class of space–time point processes. Our models are Cox processes whose stochastic intensity is a space–time Ornstein–Uhlenbeck process. We develop moment-based metho...... hiện toàn bộ
Fast Stable Restricted Maximum Likelihood and Marginal Likelihood Estimation of Semiparametric Generalized Linear Models
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 73 Số 1 - Trang 3-36 - 2011
Simon N. Wood
Summary Recent work by Reiss and Ogden provides a theoretical basis for sometimes preferring restricted maximum likelihood (REML) to generalized cross-validation (GCV) for smoothing parameter selection in semiparametric regression. However, existing REML or marginal likelihood (ML) based methods for semiparametric generalized linear models (GLMs) use...... hiện toàn bộ
Regression Shrinkage and Selection via The Lasso: A Retrospective
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 73 Số 3 - Trang 273-282 - 2011
Robert Tibshirani
Summary In the paper I give a brief review of the basic idea and some history and then discuss some developments since the original paper on regression shrinkage and selection via the lasso.
Modelling and Smoothing Parameter Estimation With Multiple Quadratic Penalties
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 62 Số 2 - Trang 413-428 - 2000
Simon N. Wood
Summary Penalized likelihood methods provide a range of practical modelling tools, including spline smoothing, generalized additive models and variants of ridge regression. Selecting the correct weights for penalties is a critical part of using these methods and in the single-penalty case the analyst has several well-founded techniques to choose from...... hiện toàn bộ
Kiểm Soát Tỷ Lệ Phát Hiện Sai: Một Cách Tiếp Cận Thực Tiễn và Mạnh Mẽ cho Kiểm Tra Đa Giả Thuyết Dịch bởi AI
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 57 Số 1 - Trang 289-300 - 1995
Yoav Benjamini, Yosef Hochberg
TÓM TẮT Cách tiếp cận phổ biến với vấn đề đa chiều yêu cầu kiểm soát tỷ lệ lỗi gia đình (FWER). Tuy nhiên, phương pháp này có những thiếu sót và chúng tôi chỉ ra một số điểm. Một cách tiếp cận khác cho các vấn đề kiểm định ý nghĩa đa tiêu chuẩn được trình bày. Phương pháp này yêu cầu kiểm soát tỷ lệ phần trăm dự kiến ​​của các giả thuyết bị bác bỏ sai — tỷ lệ phát ...... hiện toàn bộ
#Tỷ lệ lỗi gia đình #Tỷ lệ phát hiện sai #Kiểm tra đa giả thuyết #Quy trình Bonferroni #Sức mạnh kiểm định
Acceleration of the EM Algorithm by using Quasi-Newton Methods
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 59 Số 3 - Trang 569-587 - 1997
Mortaza Jamshidian, Robert I. Jennrich
Summary The EM algorithm is a popular method for maximum likelihood estimation. Its simplicity in many applications and desirable convergence properties make it very attractive. Its sometimes slow convergence, however, has prompted researchers to propose methods to accelerate it. We review these methods, classifying them into three groups: pure, hybr...... hiện toàn bộ
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