Computational Statistics

Computational inference has taken its place alongside asymptotic inference and exact techniques in the standard collection of statistical methods. Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of esti...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Gentle, James E. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Springer, 2009.
Edición:1st ed. 2009.
Colección:Statistics and Computing,
Temas:
Probabilities.
Mathematics-Data processing.
Computer science-Mathematics.
Mathematical statistics-Data processing.
Numerical analysis.
Data mining.
Probability Theory.
Computational Mathematics and Numerical Analysis.
Mathematics of Computing.
Statistics and Computing.
Numerical Analysis.
Data Mining and Knowledge Discovery.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Preliminaries
  • Mathematical and Statistical Preliminaries
  • Statistical Computing
  • Computer Storage and Arithmetic
  • Algorithms and Programming
  • Approximation of Functions and Numerical Quadrature
  • Numerical Linear Algebra
  • Solution of Nonlinear Equations and Optimization
  • Generation of Random Numbers
  • Methods of Computational Statistics
  • Graphical Methods in Computational Statistics
  • Tools for Identification of Structure in Data
  • Estimation of Functions
  • Monte Carlo Methods for Statistical Inference
  • Data Randomization, Partitioning, and Augmentation
  • Bootstrap Methods
  • Exploring Data Density and Relationships
  • Estimation of Probability Density Functions Using Parametric Models
  • Nonparametric Estimation of Probability Density Functions
  • Statistical Learning and Data Mining
  • Statistical Models of Dependencies.

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