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Visualization and Imputation of Missing Values With Applications in R /

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, inclu...

Повний опис

Збережено в:
Бібліографічні деталі
Автор: Templ, Matthias (Автор)
Співавтор: SpringerLink (Online service)
Формат: Електронний ресурс eКнига
Мова:Англійська
Опубліковано: Cham : Springer International Publishing : Imprint: Springer, 2023.
Редагування:1st ed. 2023.
Серія:Statistics and Computing,
Предмети:
Information visualization.
Statistics .
Artificial intelligence > Data processing.
Machine learning.
Mathematical statistics > Data processing.
Data and Information Visualization.
Statistical Theory and Methods.
Data Science.
Machine Learning.
Applied Statistics.
Statistics and Computing.
Онлайн доступ:https://doi.org/10.1007/978-3-031-30073-8
Теги: Додати тег
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Зміст:
  • Preface
  • 1 Topic-focused Introduction to R and Data Sets Used
  • 2 Distribution, Pre-analysis of Missing Values and Data Quality
  • 3 Detection of the Missing Values Mechanism with Tests and Models
  • 4 Visualisation of Missing Values
  • 5 General Considerations on Univariate Methods, Single and Multiple Imputation
  • 6 Deductive Imputation and Outlier Replacement
  • 7 Imputation Without a Model
  • 8 Model-based Methods
  • 9 Non-linear Methods
  • 10 Methods for compositional data
  • 11 Evaluation of the Quality of Imputation
  • 12 Simulation of Data for Simulation Studies.

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