Statistical Inference Based on the likelihood, Azzalini, Adelchi
Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Автор: Held Leonhard, Sabanйs Bovй Daniel Название: Likelihood and Bayesian Inference: With Applications in Biology and Medicine ISBN: 3662607913 ISBN-13(EAN): 9783662607916 Издательство: Springer Рейтинг: Цена: 53100.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Topics include Bayesian updating, conjugate and reference priors, Bayesian point and interval estimates, Bayesian asymptotics and empirical Bayes methods.
Автор: Tiwari, Ram Zalkikar, Jyoti (us Fda) Huang, Lan (us Fda) Название: Signal detection for medical scientists ISBN: 1032016345 ISBN-13(EAN): 9781032016344 Издательство: Taylor&Francis Рейтинг: Цена: 46950.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Tiwari, Ram (us Food And Drug Administration, Silver Spring, Md) Zalkikar, Jyoti (us Food And Drug Administration, Silver Spring, Md) Huang, Lan (us F Название: Signal detection for medical scientists ISBN: 0367201437 ISBN-13(EAN): 9780367201432 Издательство: Taylor&Francis Рейтинг: Цена: 117390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents the data mining techniques with focus on likelihood ratio test (LRT) based methods for signal detection. It emphasizes computational aspect of LRT methodology and is pertinent for first-time researchers and graduate students venturing into this interesting field.
Автор: Paul P. Eggermont; Vincent N. LaRiccia Название: Maximum Penalized Likelihood Estimation ISBN: 1461417120 ISBN-13(EAN): 9781461417125 Издательство: Springer Рейтинг: Цена: 153720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Ideal for researchers and practitioners in statistics and industrial mathematics, this book covers the theory and practice of nonparametric estimation. It is novel in its use of maximum penalized likelihood estimation and convex minimization problem theory.
Автор: Clive Loader Название: Local Regression and Likelihood ISBN: 1475772580 ISBN-13(EAN): 9781475772586 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Separation of signal from noise is the most fundamental problem in data analysis, arising in such fields as: signal processing, econometrics, actuarial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, with extensions to local likelihood and density estimation.
Автор: Vexler, Albert Название: Empirical Likelihood Methods in Biomedicine and Health ISBN: 1032401818 ISBN-13(EAN): 9781032401812 Издательство: Taylor&Francis Рейтинг: Цена: 48990.00 T Наличие на складе: Нет в наличии.
Автор: Aitkin, Murray Название: Statistical Inference ISBN: 0367383942 ISBN-13(EAN): 9780367383947 Издательство: Taylor&Francis Рейтинг: Цена: 65320.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian treatment of parameter inference and model comparisons that can be used with simple diffuse prior specifications. This novel approach provides new solutions to difficult model comparison problems and offers direct Bayesian counterparts of frequentist t-tests and other standard statistical methods for hypothesis testing.
After an overview of the competing theories of statistical inference, the book introduces the Bayes/likelihood approach used throughout. It presents Bayesian versions of one- and two-sample t-tests, along with the corresponding normal variance tests. The author then thoroughly discusses the use of the multinomial model and noninformative Dirichlet priors in "model-free" or nonparametric Bayesian survey analysis, before covering normal regression and analysis of variance. In the chapter on binomial and multinomial data, he gives alternatives, based on Bayesian analyses, to current frequentist nonparametric methods. The text concludes with new goodness-of-fit methods for assessing parametric models and a discussion of two-level variance component models and finite mixtures.
Emphasizing the principles of Bayesian inference and Bayesian model comparison, this book develops a unique methodology for solving challenging inference problems. It also includes a concise review of the various approaches to inference.
Автор: Azzalini, Adelchi Название: Statistical Inference Based on the likelihood ISBN: 041260650X ISBN-13(EAN): 9780412606502 Издательство: Taylor&Francis Рейтинг: Цена: 132710.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Pawitan, Yudi (professor Of Statistics, Department Of Statistics, National University Of Ireland, Cork) Название: In all likelihood ISBN: 0199671222 ISBN-13(EAN): 9780199671229 Издательство: Oxford Academ Рейтинг: Цена: 66530.00 T Наличие на складе: Поставка под заказ.
Автор: Schweder Название: Confidence, Likelihood, Probability ISBN: 0521861608 ISBN-13(EAN): 9780521861601 Издательство: Cambridge Academ Рейтинг: Цена: 83430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This is the first book to develop a methodology of confidence distributions, with a lively mix of theory, illustrations, applications and exercises.
Автор: Charles A. Rohde Название: Introductory Statistical Inference with the Likelihood Function ISBN: 3319374818 ISBN-13(EAN): 9783319374819 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This textbook covers the fundamentals of statistical inference and statistical theory including Bayesian and frequentist approaches and methodology possible without excessive emphasis on the underlying mathematics. The likelihood function is used for pure likelihood inference throughout the book.
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