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

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Rank-Based Procedures in Factorial Designs: Hypotheses About Non-Parametric Treatment Effects
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 79 Số 5 - Trang 1463-1485 - 2017
Edgar Brunner, Frank Konietschke, Markus Pauly, Madan L. Puri
Summary Existing tests for factorial designs in the non-parametric case are based on hypotheses formulated in terms of distribution functions. Typical null hypotheses, however, are formulated in terms of some parameters or effect measures, particularly in heteroscedastic settings. Here this idea is extended to non-parametric models by introducing a n...... hiện toàn bộ
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
Estimation and Testing Stationarity for Double-Autoregressive Models
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 66 Số 1 - Trang 63-78 - 2004
Shiqing Ling
SummaryThe paper considers the double-autoregressive model yt = φyt−1+ɛt with ɛt =ηt√(ω+αyt−12). Consistency and asymptotic normality of the estimated parameters are proved under the condition E ln |φ +√αηt|<0, which includes the cases with |φ|=1 or |φ|>1 as well as E(εt2)=∞. It is well known that all kinds of estimators of φ in these cases are not no...... 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
Towards a Coherent Statistical Framework for Dense Deformable Template Estimation
Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 69 Số 1 - Trang 3-29 - 2007
Stéphanie Allassonnière, Yali Amit, Alain Trouvé
SummaryThe problem of estimating probabilistic deformable template models in the field of computer vision or of probabilistic atlases in the field of computational anatomy has not yet received a coherent statistical formulation and remains a challenge. We provide a careful definition and analysis of a well-defined statistical model based on dense deformable templat...... 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.
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