東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Statistical disclosure control for m...

Templ, Matthias.

Linked to FindBook

Google Book

Amazon

博客來

Statistical disclosure control for microdata = methods and applications in R /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical disclosure control for microdata/ by Matthias Templ.
Reminder of title:	methods and applications in R /
Author:	Templ, Matthias.
Published:	Cham :Springer International Publishing : : 2017.,
Description:	xix, 287 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Preface -- Software -- Basic Concepts -- Disclosure Risk -- Methods for Data Perturbation -- Data Utility and Information Loss -- Synthetic Data -- Practical Guidelines -- Case Studies -- Solutions -- Index.
Contained By:	Springer eBooks
Subject:	Mathematical statistics - Data processing. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-50272-4
ISBN:	9783319502724

Statistical disclosure control for microdata = methods and applications in R /
Templ, Matthias.

Statistical disclosure control for microdatamethods and applications in R /[electronic resource] :by Matthias Templ. - Cham :Springer International Publishing :2017. - xix, 287 p. :ill. (some col.), digital ;24 cm.

Preface -- Software -- Basic Concepts -- Disclosure Risk -- Methods for Data Perturbation -- Data Utility and Information Loss -- Synthetic Data -- Practical Guidelines -- Case Studies -- Solutions -- Index.

This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and methods for simulating synthetic data. Introducing readers to the R packages sdcMicro and simPop, the book also features numerous examples and exercises with solutions, as well as case studies with real-world data, accompanied by the underlying R code to allow readers to reproduce all results. The demand for and volume of data from surveys, registers or other sources containing sensible information on persons or enterprises have increased significantly over the last several years. At the same time, privacy protection principles and regulations have imposed restrictions on the access and use of individual data. Proper and secure microdata dissemination calls for the application of statistical disclosure control methods to the data before release. This book is intended for practitioners at statistical agencies and other national and international organizations that deal with confidential data. It will also be interesting for researchers working in statistical disclosure control and the health sciences.

ISBN: 9783319502724

Standard No.: 10.1007/978-3-319-50272-4doiSubjects--Topical Terms:

532521
Mathematical statistics
--Data processing.

LC Class. No.: QA276.4 / .T46 2017

Dewey Class. No.: 519.5

Statistical disclosure control for microdata = methods and applications in R /
LDR:02456nmm a2200313 a 4500 001 2100599
003 DE-He213
005 20170505151404.0
006 m d
007 cr nn 008maaau
008 180119s2017 gw s 0 eng d
020 $a 9783319502724 $q (electronic bk.)
020 $a 9783319502700 $q (paper)
024 7 $a 10.1007/978-3-319-50272-4 $2 doi
035 $a 978-3-319-50272-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA276.4 $b .T46 2017
072 7 $a JHBC $2 bicssc
072 7 $a SOC027000 $2 bisacsh
082 0 4 $a 519.5 $2 23
090 $a QA276.4 $b .T284 2017
100 1 $a Templ, Matthias. $3 3242422
245 1 0 $a Statistical disclosure control for microdata $h [electronic resource] : $b methods and applications in R / $c by Matthias Templ.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a xix, 287 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Preface -- Software -- Basic Concepts -- Disclosure Risk -- Methods for Data Perturbation -- Data Utility and Information Loss -- Synthetic Data -- Practical Guidelines -- Case Studies -- Solutions -- Index.
520 $a This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and methods for simulating synthetic data. Introducing readers to the R packages sdcMicro and simPop, the book also features numerous examples and exercises with solutions, as well as case studies with real-world data, accompanied by the underlying R code to allow readers to reproduce all results. The demand for and volume of data from surveys, registers or other sources containing sensible information on persons or enterprises have increased significantly over the last several years. At the same time, privacy protection principles and regulations have imposed restrictions on the access and use of individual data. Proper and secure microdata dissemination calls for the application of statistical disclosure control methods to the data before release. This book is intended for practitioners at statistical agencies and other national and international organizations that deal with confidential data. It will also be interesting for researchers working in statistical disclosure control and the health sciences.
650 0 $a Mathematical statistics $x Data processing. $3 532521
650 0 $a R (Computer program language) $3 784593
650 1 4 $a Statistics. $3 517247
650 2 4 $a Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. $3 894294
650 2 4 $a Statistics and Computing/Statistics Programs. $3 894293
650 2 4 $a Statistical Theory and Methods. $3 891074
650 2 4 $a Statistics for Business/Economics/Mathematical Finance/Insurance. $3 891081
650 2 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 891086
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-50272-4
950 $a Mathematics and Statistics (Springer-11649)