Advanced R statistical programming and data models : analysis, machine learning, and visualization

Advanced R statistical programming and data models analysis, machine learning, and visualization

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples us...

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Detalles Bibliográficos
Autores principales: Wiley, Matt. author (author), Wiley, Joshua F. author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Berkeley, CA : Apress 2019.
Edición:1st ed. 2019.
Materias:
R (Llenguatge de programació)
Estadística matemàtica
Programming languages (Electronic computers).
Computer programming.
Mathematical statistics.
R (Computer program language).
Programming Languages, Compilers, Interpreters.
Programming Techniques.
Probability and Statistics in Computer Science.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630537806719
Tabla de Contenidos:
  • 1 Univariate Data Visualization
  • 2 Multivariate Data Visualization
  • 3 Generalized Linear Models 1
  • 4 Generalized Linear Models 2
  • 5 Generalized Additive Models
  • 6 Machine Learning: Introduction
  • 7 Machine Learning: Unsupervised
  • 8 Machine Learning: Supervised
  • 9 Missing Data
  • 10 Generalized Linear Mixed Models: Introduction
  • 11 Generalized Linear Mixed Models: Linear
  • 12 Generalized Linear Mixed Models: Advanced
  • 13 Modeling IIV
  • Bibliography.

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