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This book treats the latest developments in the theory of order-restricted inference, with special attention to nonparametric methods and algorithmic aspects. Among the topics treated are current status and interval censoring models, competing risk models, and deconvolution. Methods of order restricted inference are used in computing maximum likelihood estimators and developing distribution theory for inverse problems of this type. The authors have been active in developing these tools and present the state of the art and the open problems in the field. The earlier chapters provide an...

Dealing with the subject of probability theory and statistics, this text includes coverage of: inverse problems; isoperimetry and gaussian analysis; and perturbation methods of the theory of Gibbsian fields.