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Numerical Analysis for Statisticians

Every advance in computer architecture and software tempts statisticians to tackle numerically harder problems. To do so intelligently requires a good working knowledge of numerical analysis. This book equips students to craft their own software and to understand the advantages and disadvantages of...

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Bibliographic Details
Main Author: Lange, Kenneth. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic
Language:English
Published: New York, NY : Springer New York, 2010.
Series:Statistics and Computing,
Subjects:
Statistics.
Mathematical statistics.
Statistics and Computing/Statistics Programs.
Online Access:https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4419-5945-4
Table of Contents:
  • Recurrence Relations
  • Power Series Expansions
  • Continued Fraction Expansions
  • Asymptotic Expansions
  • Solution of Nonlinear Equations
  • Vector and Matrix Norms
  • Linear Regression and Matrix Inversion
  • Eigenvalues and Eigenvectors
  • Singular Value Decomposition
  • Splines
  • Optimization Theory
  • The MM Algorithm
  • The EM Algorithm
  • Newton's Method and Scoring
  • Local and Global Convergence
  • Advanced Optimization Topics
  • Concrete Hilbert Spaces
  • Quadrature Methods
  • The Fourier Transform
  • The Finite Fourier Transform
  • Wavelets
  • Generating Random Deviates
  • Independent Monte Carlo
  • Permutation Tests and the Bootstrap
  • Finite-State Markov Chains
  • Markov Chain Monte Carlo
  • Advanced Topics in MCMC.

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