國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Likelihood and Bayesian inferencewit...

Held, Leonhard.

Likelihood and Bayesian inferencewith applications in biology and medicine /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Likelihood and Bayesian inferenceby Leonhard Held, Daniel Sabanes Bove.
其他題名:	with applications in biology and medicine /
作者:	Held, Leonhard.
其他作者:	Sabanes Bove, Daniel.
出版者:	Berlin, Heidelberg :Springer Berlin Heidelberg :2020.
面頁冊數:	xiii, 402 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Bayesian statistical decision theory.
電子資源:	https://doi.org/10.1007/978-3-662-60792-3
ISBN:	9783662607923$q(electronic bk.)

Likelihood and Bayesian inferencewith applications in biology and medicine /
Held, Leonhard.

Likelihood and Bayesian inferencewith applications in biology and medicine /[electronic resource] :by Leonhard Held, Daniel Sabanes Bove. - Second edition. - Berlin, Heidelberg :Springer Berlin Heidelberg :2020. - xiii, 402 p. :ill., digital ;24 cm. - Statistics for biology and health,1431-8776. - Statistics for biology and health..

This richly illustrated textbook covers modern statistical methods with applications in medicine, epidemiology and biology. Firstly, it discusses the importance of statistical models in applied quantitative research and the central role of the likelihood function, describing likelihood-based inference from a frequentist viewpoint, and exploring the properties of the maximum likelihood estimate, the score function, the likelihood ratio and the Wald statistic. In the second part of the book, likelihood is combined with prior information to perform Bayesian inference. Topics include Bayesian updating, conjugate and reference priors, Bayesian point and interval estimates, Bayesian asymptotics and empirical Bayes methods. It includes a separate chapter on modern numerical techniques for Bayesian inference, and also addresses advanced topics, such as model choice and prediction from frequentist and Bayesian perspectives. This revised edition of the book "Applied Statistical Inference" has been expanded to include new material on Markov models for time series analysis. It also features a comprehensive appendix covering the prerequisites in probability theory, matrix algebra, mathematical calculus, and numerical analysis, and each chapter is complemented by exercises. The text is primarily intended for graduate statistics and biostatistics students with an interest in applications.

ISBN: 9783662607923$q(electronic bk.)

Standard No.: 10.1007/978-3-662-60792-3doiSubjects--Topical Terms:

182005
Bayesian statistical decision theory.

LC Class. No.: QA279.5 / .H453 2020

Dewey Class. No.: 519.542

Likelihood and Bayesian inferencewith applications in biology and medicine /
LDR:02533nmm a2200349 a 4500 001 572822
003 DE-He213
005 20200806111659.0
006 m d
007 cr nn 008maaau
008 200925s2020 gw s 0 eng d
020 $a 9783662607923$q(electronic bk.)
020 $a 9783662607916$q(paper)
024 7 $a 10.1007/978-3-662-60792-3 $2 doi
035 $a 978-3-662-60792-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QA279.5 $b .H453 2020
072 7 $a PBT $2 bicssc
072 7 $a MED090000 $2 bisacsh
072 7 $a PBT $2 thema
072 7 $a MBNS $2 thema
082 0 4 $a 519.542 $2 23
090 $a QA279.5 $b .H474 2020
100 1 $a Held, Leonhard. $3 267168
245 1 0 $a Likelihood and Bayesian inference $h [electronic resource] : $b with applications in biology and medicine / $c by Leonhard Held, Daniel Sabanes Bove.
250 $a Second edition.
260 $a Berlin, Heidelberg : $b Springer Berlin Heidelberg : $b Imprint: Springer, $c 2020.
300 $a xiii, 402 p. : $b ill., digital ; $c 24 cm.
490 1 $a Statistics for biology and health, $x 1431-8776
520 $a This richly illustrated textbook covers modern statistical methods with applications in medicine, epidemiology and biology. Firstly, it discusses the importance of statistical models in applied quantitative research and the central role of the likelihood function, describing likelihood-based inference from a frequentist viewpoint, and exploring the properties of the maximum likelihood estimate, the score function, the likelihood ratio and the Wald statistic. In the second part of the book, likelihood is combined with prior information to perform Bayesian inference. Topics include Bayesian updating, conjugate and reference priors, Bayesian point and interval estimates, Bayesian asymptotics and empirical Bayes methods. It includes a separate chapter on modern numerical techniques for Bayesian inference, and also addresses advanced topics, such as model choice and prediction from frequentist and Bayesian perspectives. This revised edition of the book "Applied Statistical Inference" has been expanded to include new material on Markov models for time series analysis. It also features a comprehensive appendix covering the prerequisites in probability theory, matrix algebra, mathematical calculus, and numerical analysis, and each chapter is complemented by exercises. The text is primarily intended for graduate statistics and biostatistics students with an interest in applications.
650 0 $a Bayesian statistical decision theory. $3 182005
650 0 $a Decision making $x Statistical methods. $3 208497
650 1 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 274067
650 2 4 $a Statistical Theory and Methods. $3 274054
650 2 4 $a Biostatistics. $3 339693
650 2 4 $a Bayesian Inference. $3 825978
650 2 4 $a Theoretical Ecology/Statistics. $3 276089
650 2 4 $a Genetics and Population Dynamics. $3 274842
700 1 $a Sabanes Bove, Daniel. $3 677408
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Statistics for biology and health. $3 558271
856 4 0 $u https://doi.org/10.1007/978-3-662-60792-3
950 $a Mathematics and Statistics (Springer-11649)