The aim of statistical disclosure control is to keep up the required statistical privacy while making data available to the researchers. This can be achieved with the help of minimal modifications of the data without changing the multivariate data structure. In this book the well-developed R package sdc- Micro is introduced. With the help of this package it is possible to keep microdata confidential in a very effective way. The concept is thoroughly explained and its application is demonstrated using real-world data. In addition to that, the robustification of disclosure methods is described....
The aim of statistical disclosure control is to keep up the required statistical privacy while making data available to the researchers. This can ...
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...
This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)dat...
This book presents the statistical analysis of compositional data using the log-ratio approach. It includes a wide range of classical and robust statistical methods adapted for compositional data analysis, such as supervised and unsupervised methods like PCA, correlation analysis, classification and regression.
This book presents the statistical analysis of compositional data using the log-ratio approach. It includes a wide range of classical and robust stati...
