Selected Statistical Papers of Sir David Cox: Volume 2, Foundations of Statistical Inference, Theoretical Statistics, Time Series and Stochastic Processes PDF Download
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Author: David Roxbee Cox
Publisher: Cambridge University Press
ISBN: 9780521849401
Category : Business & Economics
Languages : en
Pages : 614
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Book Description
Sir David Cox's most important papers, each the subject of a new commentary by Professor Cox.
Author: David Roxbee Cox
Publisher: Cambridge University Press
ISBN: 9780521849401
Category : Business & Economics
Languages : en
Pages : 614
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Book Description
Sir David Cox's most important papers, each the subject of a new commentary by Professor Cox.
Author: Cox, David Roxbee Cox
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: David Roxbee Cox
Publisher: Cambridge University Press
ISBN: 9780521849395
Category : Business & Economics
Languages : en
Pages : 620
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Book Description
Sir David Cox's most important papers, each the subject of a new commentary by Professor Cox.
Author: D. R. Cox
Publisher: Cambridge University Press
ISBN: 1139459139
Category : Mathematics
Languages : en
Pages : 227
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Book Description
In this definitive book, D. R. Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more personal assessment of the merits of different ideas. The content ranges from the traditional to the contemporary. While specific applications are not treated, the book is strongly motivated by applications across the sciences and associated technologies. The mathematics is kept as elementary as feasible, though previous knowledge of statistics is assumed. The book will be valued by every user or student of statistics who is serious about understanding the uncertainty inherent in conclusions from statistical analyses.
Author: American Statistical Association
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 434
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Author:
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 1164
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Book Description
Author: D.V. Hinkley
Publisher: Chapman and Hall/CRC
ISBN:
Category : Mathematics
Languages : en
Pages : 386
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Book Description
Statistical Theory and Modelling is a celebration of the work of Sir David Cox, FRS, and reflects his many interests in statistical theory and methods. It is a series of review articles, intended as an introduction to a variety of topics suitable for the graduate student and practicing statistician. Many of the topics are the subject of book-length treatments by Sir David and authors of this volume. Each chapter leads to a larger literature. Topics range the breadth of statistics and include modern degvelopments in statistical theory and methods. Special topics covered are generalized linear models, residuals and diagnostics, survival analysis, sequential analysis, time series, stochastic modelling of spatial data, design of experiments, likelihood inference and statistical approximation.
Author: Arthur James Wells
Publisher:
ISBN:
Category : Bibliography, National
Languages : en
Pages : 2492
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Book Description
Author: Dennis D. Boos
Publisher: Springer
ISBN: 9781489987938
Category : Mathematics
Languages : en
Pages : 0
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Book Description
This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems. An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology. Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods.
Author: David R. Cox
Publisher:
ISBN:
Category :
Languages : en
Pages : 511
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Book Description
