東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ subject:"Statistical astronomy." ]

切換: 標籤 | MARC模式 | ISBD

Bayesian methods for the physical sc...

Andreon, Stefano.

FindBook

Google Book

Amazon

博客來

Bayesian methods for the physical sciences = learning from examples in astronomy and physics /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Bayesian methods for the physical sciences/ by Stefano Andreon, Brian Weaver.
其他題名:	learning from examples in astronomy and physics /
作者:	Andreon, Stefano.
其他作者:	Weaver, Brian.
出版者:	Cham :Springer International Publishing : : 2015.,
面頁冊數:	xi, 238 p. :ill. (some col.), digital ;24 cm.
內容註:	Recipes -- A Bit of Theory -- A Bit of Numerical Computation -- Single Parameter Models -- The Prior -- Multi-parameters Models -- Non-random Data Collection -- Fitting Regression Models -- Model Checking and Sensitivity Analysis -- Bayesian vs Simple Methods -- Appendix: Probability Distributions -- Appendix: The third axiom of probability, conditional probability, independence and conditional independence.
Contained By:	Springer eBooks
標題:	Bayesian statistical decision theory. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-15287-5
ISBN:	9783319152875 (electronic bk.)

Bayesian methods for the physical sciences = learning from examples in astronomy and physics /
Andreon, Stefano.

Bayesian methods for the physical scienceslearning from examples in astronomy and physics /[electronic resource] :by Stefano Andreon, Brian Weaver. - Cham :Springer International Publishing :2015. - xi, 238 p. :ill. (some col.), digital ;24 cm. - Springer series in astrostatistics,2199-1030. - Springer series in astrostatistics..

Recipes -- A Bit of Theory -- A Bit of Numerical Computation -- Single Parameter Models -- The Prior -- Multi-parameters Models -- Non-random Data Collection -- Fitting Regression Models -- Model Checking and Sensitivity Analysis -- Bayesian vs Simple Methods -- Appendix: Probability Distributions -- Appendix: The third axiom of probability, conditional probability, independence and conditional independence.

Statistical literacy is critical for the modern researcher in Physics and Astronomy. This book empowers researchers in these disciplines by providing the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of real-world problems taken from modern astronomical research. The examples are intended to be starting points for readers as they learn to approach their own data and research questions. Acknowledging that scientific progress now hinges on the availability of data and the possibility to improve previous analyses, data and code are distributed throughout the book. The JAGS symbolic language used throughout the book makes it easy to perform Bayesian analysis and is particularly valuable as readers may use it in a myriad of scenarios through slight modifications. This book is comprehensive, well written, and will surely be regarded as a standard text in both astrostatistics and physical statistics. Joseph M. Hilbe, President, International Astrostatistics Association, Professor Emeritus, University of Hawaii, and Adjunct Professor of Statistics, Arizona State University.

ISBN: 9783319152875 (electronic bk.)

Standard No.: 10.1007/978-3-319-15287-5doiSubjects--Topical Terms:

551404
Bayesian statistical decision theory.

LC Class. No.: QC20.7.B38

Dewey Class. No.: 519.542

Bayesian methods for the physical sciences = learning from examples in astronomy and physics /
LDR:02766nmm a2200337 a 4500 001 2006517
003 DE-He213
005 20160105112840.0
006 m d
007 cr nn 008maaau
008 160114s2015 gw s 0 eng d
020 $a 9783319152875 (electronic bk.)
020 $a 9783319152868 (paper)
024 7 $a 10.1007/978-3-319-15287-5 $2 doi
035 $a 978-3-319-15287-5
040 $a GP $c GP
041 0 $a eng
050 4 $a QC20.7.B38
072 7 $a PBT $2 bicssc
072 7 $a PD $2 bicssc
072 7 $a MAT029000 $2 bisacsh
082 0 4 $a 519.542 $2 23
090 $a QC20.7.B38 $b A559 2015
100 1 $a Andreon, Stefano. $3 2153480
245 1 0 $a Bayesian methods for the physical sciences $h [electronic resource] : $b learning from examples in astronomy and physics / $c by Stefano Andreon, Brian Weaver.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a xi, 238 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Springer series in astrostatistics, $x 2199-1030
505 0 $a Recipes -- A Bit of Theory -- A Bit of Numerical Computation -- Single Parameter Models -- The Prior -- Multi-parameters Models -- Non-random Data Collection -- Fitting Regression Models -- Model Checking and Sensitivity Analysis -- Bayesian vs Simple Methods -- Appendix: Probability Distributions -- Appendix: The third axiom of probability, conditional probability, independence and conditional independence.
520 $a Statistical literacy is critical for the modern researcher in Physics and Astronomy. This book empowers researchers in these disciplines by providing the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of real-world problems taken from modern astronomical research. The examples are intended to be starting points for readers as they learn to approach their own data and research questions. Acknowledging that scientific progress now hinges on the availability of data and the possibility to improve previous analyses, data and code are distributed throughout the book. The JAGS symbolic language used throughout the book makes it easy to perform Bayesian analysis and is particularly valuable as readers may use it in a myriad of scenarios through slight modifications. This book is comprehensive, well written, and will surely be regarded as a standard text in both astrostatistics and physical statistics. Joseph M. Hilbe, President, International Astrostatistics Association, Professor Emeritus, University of Hawaii, and Adjunct Professor of Statistics, Arizona State University.
650 0 $a Bayesian statistical decision theory. $3 551404
650 0 $a Mathematical physics. $3 516853
650 0 $a Statistical astronomy. $3 2012802
650 1 4 $a Statistics. $3 517247
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 1005896
650 2 4 $a Astronomy, Astrophysics and Cosmology. $3 890823
650 2 4 $a Mathematical Methods in Physics. $3 890898
700 1 $a Weaver, Brian. $3 2153481
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Springer series in astrostatistics. $3 2153482
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-15287-5
950 $a Mathematics and Statistics (Springer-11649)