Visualization And Imputation Of Missing Values

Author : Matthias Templ
Publisher : Springer Nature
ISBN 13 : 3031300734
Total Pages : 478 pages
Book Rating : 4.38/5 ( download)

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Download or read book Visualization and Imputation of Missing Values written by Matthias Templ and published by Springer Nature. This book was released on 2023-11-29 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Stef van Buuren
Publisher : CRC Press
ISBN 13 : 0429960352
Total Pages : 444 pages
Book Rating : 4.52/5 ( download)

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Download or read book Flexible Imputation of Missing Data, Second Edition written by Stef van Buuren and published by CRC Press. This book was released on 2018-07-17 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.

Author : Max Kuhn
Publisher : CRC Press
ISBN 13 : 1351609467
Total Pages : 266 pages
Book Rating : 4.63/5 ( download)

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Download or read book Feature Engineering and Selection written by Max Kuhn and published by CRC Press. This book was released on 2019-07-25 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

Author : Deborah F. Swayne
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.43/5 ( download)

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Download or read book Missing Data in Interactive High-Dimensional Data Visualization written by Deborah F. Swayne and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We describe techniques for the interactive exploratory analysis of multi-variate data with missing values. The approach is to 1) provide trivial imputations such as fixed values, 2) accept multiple imputations computed elsewhere, and 3) provide a means for keeping track of the location of missing values in the data. The techniques have two major uses: First, they support the exploration of missing values, their correlations across variables and their associations with the variables of interest. Second, the techniques support the investigation and comparison of precomputed imputation schemes; in particular, they can be used to informally diagnose the adequacy of imputations. The techniques are illustrated with an implementation in the Xgobi software.

Author : Dianne Cook
Publisher : Springer Science & Business Media
ISBN 13 : 0387717617
Total Pages : 202 pages
Book Rating : 4.16/5 ( download)

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Download or read book Interactive and Dynamic Graphics for Data Analysis written by Dianne Cook and published by Springer Science & Business Media. This book was released on 2007-12-12 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about using interactive and dynamic plots on a computer screen as part of data exploration and modeling, both alone and as a partner with static graphics and non-graphical computational methods. The area of int- active and dynamic data visualization emerged within statistics as part of research on exploratory data analysis in the late 1960s, and it remains an active subject of research today, as its use in practice continues to grow. It now makes substantial contributions within computer science as well, as part of the growing ?elds of information visualization and data mining, especially visual data mining. The material in this book includes: • An introduction to data visualization, explaining how it di?ers from other types of visualization. • Adescriptionofourtoolboxofinteractiveanddynamicgraphicalmethods. • An approach for exploring missing values in data. • An explanation of the use of these tools in cluster analysis and supervised classi?cation. • An overview of additional material available on the web. • A description of the data used in the analyses and exercises. The book’s examples use the software R and GGobi. R (Ihaka & Gent- man 1996, RDevelopment CoreTeam2006) isafreesoftware environment for statistical computing and graphics; it is most often used from the command line, provides a wide variety of statistical methods, and includes high–quality staticgraphics.RaroseintheStatisticsDepartmentoftheUniversityofAu- land and is now developed and maintained by a global collaborative e?ort.

Author : Thomas Frederick Coleman
Publisher : SIAM
ISBN 13 : 9780898712681
Total Pages : 278 pages
Book Rating : 4.88/5 ( download)

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Download or read book Large-scale Numerical Optimization written by Thomas Frederick Coleman and published by SIAM. This book was released on 1990-01-01 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Papers from a workshop held at Cornell University, Oct. 1989, and sponsored by Cornell's Mathematical Sciences Institute. Annotation copyright Book News, Inc. Portland, Or.

Author : Graham Wills
Publisher : Springer Science & Business Media
ISBN 13 : 0387779078
Total Pages : 269 pages
Book Rating : 4.72/5 ( download)

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Download or read book Visualizing Time written by Graham Wills and published by Springer Science & Business Media. This book was released on 2011-12-02 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Art, or Science? Which of these is the right way to think of the field of visualization? This is not an easy question to answer, even for those who have many years experience in making graphical depictions of data with a view to help people understand it and take action. In this book, Graham Wills bridges the gap between the art and the science of visually representing data. He does not simply give rules and advice, but bases these on general principles and provide a clear path between them This book is concerned with the graphical representation of time data and is written to cover a range of different users. A visualization expert designing tools for displaying time will find it valuable, but so also should a financier assembling a report in a spreadsheet, or a medical researcher trying to display gene sequences using a commercial statistical package.

Author : Paul D. Allison
Publisher : SAGE Publications
ISBN 13 : 1071962523
Total Pages : 100 pages
Book Rating : 4.27/5 ( download)

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Download or read book Missing Data written by Paul D. Allison and published by SAGE Publications. This book was released on 2024-05-08 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sooner or later anyone who does statistical analysis runs into problems with missing data in which information for some variables is missing for some cases. Why is this a problem? Because most statistical methods presume that every case has information on all the variables to be included in the analysis. Using numerous examples and practical tips, this book offers a nontechnical explanation of the standard methods for missing data (such as listwise or casewise deletion) as well as two newer (and, better) methods, maximum likelihood and multiple imputation. Anyone who has been relying on ad-hoc methods that are statistically inefficient or biased will find this book a welcome and accessible solution to their problems with handling missing data.

Author : International Federation of Classification Societies. Conference
Publisher : Springer Science & Business Media
ISBN 13 : 3540220143
Total Pages : 676 pages
Book Rating : 4.45/5 ( download)

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Download or read book Classification, Clustering, and Data Mining Applications written by International Federation of Classification Societies. Conference and published by Springer Science & Business Media. This book was released on 2004-06-09 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern data analysis stands at the interface of statistics, computer science, and discrete mathematics. This volume describes new methods in this area, with special emphasis on classification and cluster analysis. Those methods are applied to problems in information retrieval, phylogeny, medical diagnosis, microarrays, and other active research areas.

Author : Richard McElreath
Publisher : CRC Press
ISBN 13 : 1315362619
Total Pages : 488 pages
Book Rating : 4.18/5 ( download)

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Download or read book Statistical Rethinking written by Richard McElreath and published by CRC Press. This book was released on 2018-01-03 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.