國立高雄大學圖資館 |

Language: English

Back

Advances in complex data modeling an...

Paganoni, Anna Maria.

Advances in complex data modeling and computational methods in statistics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advances in complex data modeling and computational methods in statisticsedited by Anna Maria Paganoni, Piercesare Secchi.
other author:	Paganoni, Anna Maria.
Published:	Cham :Springer International Publishing :2015.
Description:	viii, 209 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Mathematical statisticsData processing.
Online resource:	http://dx.doi.org/10.1007/978-3-319-11149-0
ISBN:	9783319111490 (electronic bk.)

Advances in complex data modeling and computational methods in statistics
Advances in complex data modeling and computational methods in statistics[electronic resource] /edited by Anna Maria Paganoni, Piercesare Secchi. - Cham :Springer International Publishing :2015. - viii, 209 p. :ill. (some col.), digital ;24 cm. - Contributions to statistics,1431-1968. - Contributions to statistics..

The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.

ISBN: 9783319111490 (electronic bk.)

Standard No.: 10.1007/978-3-319-11149-0doiSubjects--Topical Terms:

183916
Mathematical statistics
--Data processing.

LC Class. No.: QA276.4 / .A38 2015

Dewey Class. No.: 519.5

Advances in complex data modeling and computational methods in statistics
LDR:02171nmm a2200313 a 4500 001 460730
003 DE-He213
005 20150713104557.0
006 m d
007 cr nn 008maaau
008 151110s2015 gw s 0 eng d
020 $a 9783319111490 (electronic bk.)
020 $a 9783319111483 (paper)
024 7 $a 10.1007/978-3-319-11149-0 $2 doi
035 $a 978-3-319-11149-0
040 $a GP $c GP
041 0 $a eng
050 4 $a QA276.4 $b .A38 2015
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
082 0 4 $a 519.5 $2 23
090 $a QA276.4 $b .A244 2015
245 0 0 $a Advances in complex data modeling and computational methods in statistics $h [electronic resource] / $c edited by Anna Maria Paganoni, Piercesare Secchi.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a viii, 209 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Contributions to statistics, $x 1431-1968
520 $a The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.
650 0 $a Mathematical statistics $x Data processing. $3 183916
650 1 4 $a Statistics. $3 182057
650 2 4 $a Statistical Theory and Methods. $3 274054
650 2 4 $a Applications of Mathematics. $3 273744
650 2 4 $a Biostatistics. $3 339693
650 2 4 $a Complexity. $3 274400
650 2 4 $a Software Engineering/Programming and Operating Systems. $3 273711
700 1 $a Paganoni, Anna Maria. $3 712347
700 1 $a Secchi, Piercesare. $3 497833
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Contributions to statistics. $3 593379
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-11149-0
950 $a Mathematics and Statistics (Springer-11649)