Visualization and Imputation of Missing Values

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Visualization and Imputation of Missing Values
Περιγραφή: 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.
Συγγραφείς: Matthias Templ
Resource Type: eBook.
Θέματα: Information visualization--Data processing, R (Computer program language), Missing observations (Statistics)--Data processing
Categories: MATHEMATICS / Graphic Methods, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Database Administration & Management, COMPUTERS / Mathematical & Statistical Software, MATHEMATICS / Probability & Statistics / General
Βάση Δεδομένων: eBook Index
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DbLabel: eBook Index
An: 3748795
RelevancyScore: 969
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 968.509704589844
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  Data: 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.
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RecordInfo BibRecord:
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      – Code: 001.422602855133
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Information visualization--Data processing
        Type: general
      – SubjectFull: R (Computer program language)
        Type: general
      – SubjectFull: Missing observations (Statistics)--Data processing
        Type: general
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      – TitleFull: Visualization and Imputation of Missing Values
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            NameFull: Matthias Templ
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2023
            – D: 01
              M: 12
              Type: profile
              Y: 2023
          Identifiers:
            – Type: isbn-print
              Value: 9783031300721
            – Type: isbn-electronic
              Value: 9783031300738
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            – TitleFull: Visualization and Imputation of Missing Values
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