Synthetic Datasets For Statistical Disclosure Control
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Synthetic Datasets For Statistical Disclosure Control
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Author : J. Rg Drechsler
language : en
Publisher:
Release Date : 2011-06-26
Synthetic Datasets For Statistical Disclosure Control written by J. Rg Drechsler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-26 with categories.
Synthetic Datasets For Statistical Disclosure Control
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Author : Jörg Drechsler
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-24
Synthetic Datasets For Statistical Disclosure Control written by Jörg Drechsler and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-24 with Social Science categories.
The aim of this book is to give the reader a detailed introduction to the different approaches to generating multiply imputed synthetic datasets. It describes all approaches that have been developed so far, provides a brief history of synthetic datasets, and gives useful hints on how to deal with real data problems like nonresponse, skip patterns, or logical constraints. Each chapter is dedicated to one approach, first describing the general concept followed by a detailed application to a real dataset providing useful guidelines on how to implement the theory in practice. The discussed multiple imputation approaches include imputation for nonresponse, generating fully synthetic datasets, generating partially synthetic datasets, generating synthetic datasets when the original data is subject to nonresponse, and a two-stage imputation approach that helps to better address the omnipresent trade-off between analytical validity and the risk of disclosure. The book concludes with a glimpse into the future of synthetic datasets, discussing the potential benefits and possible obstacles of the approach and ways to address the concerns of data users and their understandable discomfort with using data that doesn’t consist only of the originally collected values. The book is intended for researchers and practitioners alike. It helps the researcher to find the state of the art in synthetic data summarized in one book with full reference to all relevant papers on the topic. But it is also useful for the practitioner at the statistical agency who is considering the synthetic data approach for data dissemination in the future and wants to get familiar with the topic.
Statistical Disclosure Control For Microdata
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Author : Matthias Templ
language : en
Publisher: Springer
Release Date : 2017-05-05
Statistical Disclosure Control For Microdata written by Matthias Templ and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-05 with Social Science categories.
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 da ta 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.
Statistical Disclosure Control
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Author : Anco Hundepool
language : en
Publisher: John Wiley & Sons
Release Date : 2012-07-05
Statistical Disclosure Control written by Anco Hundepool and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-05 with Mathematics categories.
A reference to answer all your statistical confidentiality questions. This handbook provides technical guidance on statistical disclosure control and on how to approach the problem of balancing the need to provide users with statistical outputs and the need to protect the confidentiality of respondents. Statistical disclosure control is combined with other tools such as administrative, legal and IT in order to define a proper data dissemination strategy based on a risk management approach. The key concepts of statistical disclosure control are presented, along with the methodology and software that can be used to apply various methods of statistical disclosure control. Numerous examples and guidelines are also featured to illustrate the topics covered. Statistical Disclosure Control: Presents a combination of both theoretical and practical solutions Introduces all the key concepts and definitions involved with statistical disclosure control. Provides a high level overview of how to approach problems associated with confidentiality. Provides a broad-ranging review of the methods available to control disclosure. Explains the subtleties of group disclosure control. Features examples throughout the book along with case studies demonstrating how particular methods are used. Discusses microdata, magnitude and frequency tabular data, and remote access issues. Written by experts within leading National Statistical Institutes. Official statisticians, academics and market researchers who need to be informed and make decisions on disclosure limitation will benefit from this book.
Privacy In Statistical Databases
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Author : Josep Domingo-Ferrer
language : en
Publisher: Springer Nature
Release Date : 2024-09-12
Privacy In Statistical Databases written by Josep Domingo-Ferrer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-12 with Computers categories.
This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2024, held in Antibes Juan-les-Pins, France, during September 25-27, 2024. The 28 papers presented in this volume were carefully reviewed and selected from 46 submissions. They were organized in topical sections as follows: Privacy models and concepts; Microdata protection; Statistical table protection; Synthetic data generation methods; Synthetic data generation software; Disclosure risk assessment; Spatial and georeferenced data; Machine learning and privacy; and Case studies.
Data Privacy
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Author : Nataraj Venkataramanan
language : en
Publisher: CRC Press
Release Date : 2016-10-03
Data Privacy written by Nataraj Venkataramanan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-03 with Computers categories.
The book covers data privacy in depth with respect to data mining, test data management, synthetic data generation etc. It formalizes principles of data privacy that are essential for good anonymization design based on the data format and discipline. The principles outline best practices and reflect on the conflicting relationship between privacy and utility. From a practice standpoint, it provides practitioners and researchers with a definitive guide to approach anonymization of various data formats, including multidimensional, longitudinal, time-series, transaction, and graph data. In addition to helping CIOs protect confidential data, it also offers a guideline as to how this can be implemented for a wide range of data at the enterprise level.
Healthcare Data Analytics
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Author : Chandan K. Reddy
language : en
Publisher: CRC Press
Release Date : 2015-06-23
Healthcare Data Analytics written by Chandan K. Reddy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-23 with Business & Economics categories.
At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available
Practical Synthetic Data Generation
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Author : Khaled El Emam
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-05-19
Practical Synthetic Data Generation written by Khaled El Emam and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-19 with Computers categories.
Building and testing machine learning models requires access to large and diverse data. But where can you find usable datasets without running into privacy issues? This practical book introduces techniques for generating synthetic data—fake data generated from real data—so you can perform secondary analysis to do research, understand customer behaviors, develop new products, or generate new revenue. Data scientists will learn how synthetic data generation provides a way to make such data broadly available for secondary purposes while addressing many privacy concerns. Analysts will learn the principles and steps for generating synthetic data from real datasets. And business leaders will see how synthetic data can help accelerate time to a product or solution. This book describes: Steps for generating synthetic data using multivariate normal distributions Methods for distribution fitting covering different goodness-of-fit metrics How to replicate the simple structure of original data An approach for modeling data structure to consider complex relationships Multiple approaches and metrics you can use to assess data utility How analysis performed on real data can be replicated with synthetic data Privacy implications of synthetic data and methods to assess identity disclosure
Visualization And Imputation Of Missing Values
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Author : Matthias Templ
language : en
Publisher: Springer Nature
Release Date : 2023-11-29
Visualization And Imputation Of Missing Values written by Matthias Templ and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-29 with Mathematics categories.
This book explores visualization and imputation techniques for missing values and presents practical applications using the statistical software R. It explains the concepts of common imputation methods with a focus on visualization, description of data problems and practical solutions using R, including modern methods of robust imputation, imputation based on deep learning and imputation for complex data. By describing the advantages, disadvantages and pitfalls of each method, the book presents a clear picture of which imputation methods are applicable given a specific data set at hand. The material covered includes the pre-analysis of data, visualization of missing values in incomplete data, single and multiple imputation, deductive imputation and outlier replacement, model-based methods including methods based on robust estimates, non-linear methods such as tree-based and deep learning methods, imputation of compositional data, imputation quality evaluation from visual diagnostics to precision measures, coverage rates and prediction performance and a description of different model- and design-based simulation designs for the evaluation. The book also features a topic-focused introduction to R and R code is provided in each chapter to explain the practical application of the described methodology. Addressed to researchers, practitioners and students who work with incomplete data, the book offers an introduction to the subject as well as a discussion of recent developments in the field. It is suitable for beginners to the topic and advanced readers alike.
Statistical Modeling And Applications
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Author : Carlos A. Coelho
language : en
Publisher: Springer Nature
Release Date : 2024-12-17
Statistical Modeling And Applications written by Carlos A. Coelho and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-17 with Mathematics categories.
In an era defined by the seamless integration of data and sophisticated analytical and modeling techniques, the quest for advanced statistical modeling and methodologies has never been more pertinent. Statistical Modeling and Applications: Multivariate, Heavy-Tailed, Skewed Distributions, Mixture and Neural-Network Modeling, Volume 2, represents a concerted effort to bridge the gap between theoretical advancements and practical applications in the realm of Statistical Science, namely in the area of Statistical Modeling. It also aims to present a wide range of emerging topics in mathematical and statistical modeling written by a group of distinguished researchers from top-tier universities and research institutes to offer broader opportunities in stimulating further collaborations in the areas of mathematics and statistics. The book has eleven chapters, divided in two Parts, with Part I comprising five chapters dealing with the application of Multivariate Analysis techniques and multivariate distributions to a set of different situations, and Part II consisting of six chapters which address the modeling of several interesting phenomena through the use of Heavy-Tailed, Skewed, Circular-Linear and Mixture Distributions, as well as Neural Networks.