Data Fusion Through Statistical Matching
DOWNLOAD
Download Data Fusion Through Statistical Matching PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Data Fusion Through Statistical Matching book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Data Fusion Through Statistical Matching
DOWNLOAD
Author : Peter van der Putten
language : en
Publisher:
Release Date : 2005
Data Fusion Through Statistical Matching written by Peter van der Putten and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
In data mining applications, the availability of data is often a serious problem. For instance, elementary customer information resides in customer databases, but market survey data are only available for a subset of the customers or even for a different sample of customers. Data fusion provides a way out by combining information from different sources into a single data set for further data mining. While a significant amount of work has been done on data fusion in the past, most of the research has been performed outside of the data mining community. In this paper, we provide an overview of data fusion, introduce basic terminology and the statistical matching approach, distinguish between internal and external evaluation, and we conclude with a larger case study.
Data Fusion Through Statistical Matching Classic Reprint
DOWNLOAD
Author : Peter van der Puttan
language : en
Publisher: Forgotten Books
Release Date : 2016-12-06
Data Fusion Through Statistical Matching Classic Reprint written by Peter van der Puttan and has been published by Forgotten Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-06 with Mathematics categories.
Excerpt from Data Fusion Through Statistical Matching One may claim that the exponential growth in the amount of data provides great Opportunities for data mining. Reality can be different though. In many real world applications, the number of sources over which this information is fragmented grows at an even faster rate, resulting in barriers to widespread application of data mining and missed business opportunities. Let us illustrate this paradox with a motivating example from database marketing. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
Data Fusion Through Statistical Matching
DOWNLOAD
Author : Peter Van Der Puttan
language : en
Publisher: Hardpress Publishing
Release Date : 2013-12
Data Fusion Through Statistical Matching written by Peter Van Der Puttan and has been published by Hardpress Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12 with categories.
Unlike some other reproductions of classic texts (1) We have not used OCR(Optical Character Recognition), as this leads to bad quality books with introduced typos. (2) In books where there are images such as portraits, maps, sketches etc We have endeavoured to keep the quality of these images, so they represent accurately the original artefact. Although occasionally there may be certain imperfections with these old texts, we feel they deserve to be made available for future generations to enjoy.
Data Fusion Through Statistical Matching
DOWNLOAD
Author : Peter Van Der Puttan
language : en
Publisher: Legare Street Press
Release Date : 2022-10-27
Data Fusion Through Statistical Matching written by Peter Van Der Puttan and has been published by Legare Street Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-27 with categories.
This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Data Fusion And Matching By Maximizing Statistical Dependencies
DOWNLOAD
Author : Abhishek Tripathi
language : en
Publisher:
Release Date : 2011
Data Fusion And Matching By Maximizing Statistical Dependencies written by Abhishek Tripathi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Statistical Data Fusion
DOWNLOAD
Author : Kedem Benjamin
language : en
Publisher: World Scientific
Release Date : 2017-01-24
Statistical Data Fusion written by Kedem Benjamin and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-24 with Mathematics categories.
This book comes up with estimates or decisions based on multiple data sources as opposed to more narrowly defined estimates or decisions based on single data sources. And as the world is awash with data obtained from numerous and varied processes, there is a need for appropriate statistical methods which in general produce improved inference by multiple data sources. The book contains numerous examples useful to practitioners from genomics. Topics range from sensors (radars), to small area estimation of body mass, to the estimation of small tail probabilities, to predictive distributions in time series analysis.
Statistical Matching
DOWNLOAD
Author : Susanne Rässler
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Statistical Matching written by Susanne Rässler 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 2012-12-06 with Mathematics categories.
Government policy questions and media planning tasks may be answered by this data set. It covers a wide range of different aspects of statistical matching that in Europe typically is called data fusion. A book about statistical matching will be of interest to researchers and practitioners, starting with data collection and the production of public use micro files, data banks, and data bases. People in the areas of database marketing, public health analysis, socioeconomic modeling, and official statistics will find it useful.
Analysis Of Integrated Data
DOWNLOAD
Author : Li-Chun Zhang
language : en
Publisher: CRC Press
Release Date : 2019-04-18
Analysis Of Integrated Data written by Li-Chun Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-18 with Mathematics categories.
The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable statistical inference, or to generate new statistical data for purposes that cannot be served by each source on its own. This can yield significant gains for scientific as well as commercial investigations. However, valid analysis of such data should allow for the additional uncertainty due to entity ambiguity, whenever it is not possible to state with certainty that the integrated source is the target population of interest. Analysis of Integrated Data aims to provide a solid theoretical basis for this statistical analysis in three generic settings of entity ambiguity: statistical analysis of linked datasets that may contain linkage errors; datasets created by a data fusion process, where joint statistical information is simulated using the information in marginal data from non-overlapping sources; and estimation of target population size when target units are either partially or erroneously covered in each source. Covers a range of topics under an overarching perspective of data integration. Focuses on statistical uncertainty and inference issues arising from entity ambiguity. Features state of the art methods for analysis of integrated data. Identifies the important themes that will define future research and teaching in the statistical analysis of integrated data. Analysis of Integrated Data is aimed primarily at researchers and methodologists interested in statistical methods for data from multiple sources, with a focus on data analysts in the social sciences, and in the public and private sectors.
Data Fusion Concepts And Ideas
DOWNLOAD
Author : H B Mitchell
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-09
Data Fusion Concepts And Ideas written by H B Mitchell 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 2012-02-09 with Technology & Engineering categories.
This textbook provides a comprehensive introduction to the concepts and idea of multisensor data fusion. It is an extensively revised second edition of the author's successful book: "Multi-Sensor Data Fusion: An Introduction" which was originally published by Springer-Verlag in 2007. The main changes in the new book are: New Material: Apart from one new chapter there are approximately 30 new sections, 50 new examples and 100 new references. At the same time, material which is out-of-date has been eliminated and the remaining text has been rewritten for added clarity. Altogether, the new book is nearly 70 pages longer than the original book. Matlab code: Where appropriate we have given details of Matlab code which may be downloaded from the worldwide web. In a few places, where such code is not readily available, we have included Matlab code in the body of the text. Layout. The layout and typography has been revised. Examples and Matlab code now appear on a gray background for easy identification and advancd material is marked with an asterisk. The book is intended to be self-contained. No previous knowledge of multi-sensor data fusion is assumed, although some familarity with the basic tools of linear algebra, calculus and simple probability is recommended. Although conceptually simple, the study of mult-sensor data fusion presents challenges that are unique within the education of the electrical engineer or computer scientist. To become competent in the field the student must become familiar with tools taken from a wide range of diverse subjects including: neural networks, signal processing, statistical estimation, tracking algorithms, computer vision and control theory. All too often, the student views multi-sensor data fusion as a miscellaneous assortment of different processes which bear no relationship to each other. In contrast, in this book the processes are unified by using a common statistical framework. As a consequence, the underlying pattern of relationships that exists between the different methodologies is made evident. The book is illustrated with many real-life examples taken from a diverse range of applications and contains an extensive list of modern references.
Statistical Matching
DOWNLOAD
Author : Marcello D'Orazio
language : en
Publisher: John Wiley & Sons
Release Date : 2006-03-30
Statistical Matching written by Marcello D'Orazio 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 2006-03-30 with Mathematics categories.
There is more statistical data produced in today’s modern society than ever before. This data is analysed and cross-referenced for innumerable reasons. However, many data sets have no shared element and are harder to combine and therefore obtain any meaningful inference from. Statistical matching allows just that; it is the art of combining information from different sources (particularly sample surveys) that contain no common unit. In response to modern influxes of data, it is an area of rapidly growing interest and complexity. Statistical Matching: Theory and Practice introduces the basics of statistical matching, before going on to offer a detailed, up-to-date overview of the methods used and an examination of their practical applications. Presents a unified framework for both theoretical and practical aspects of statistical matching. Provides a detailed description covering all the steps needed to perform statistical matching. Contains a critical overview of the available statistical matching methods. Discusses all the major issues in detail, such as the Conditional Independence Assumption and the assessment of uncertainty. Includes numerous examples and applications, enabling the reader to apply the methods in their own work. Features an appendix detailing algorithms written in the R language. Statistical Matching: Theory and Practice presents a comprehensive exploration of an increasingly important area. Ideal for researchers in national statistics institutes and applied statisticians, it will also prove to be an invaluable text for scientists and researchers from all disciplines engaged in the multivariate analysis of data collected from different sources.