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Mastering Scientific Computing with R

You're reading from   Mastering Scientific Computing with R Employ professional quantitative methods to answer scientific questions with a powerful open source data analysis environment

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781783555253
Length 432 pages
Edition 1st Edition
Languages
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Author (1):
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Paul Gerrard Paul Gerrard
Author Profile Icon Paul Gerrard
Paul Gerrard
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Toc

Table of Contents (12) Chapters Close

Preface 1. Programming with R FREE CHAPTER 2. Statistical Methods with R 3. Linear Models 4. Nonlinear Methods 5. Linear Algebra 6. Principal Component Analysis and the Common Factor Model 7. Structural Equation Modeling and Confirmatory Factor Analysis 8. Simulations 9. Optimization 10. Advanced Data Management Index

Index

A

  • abline() function / Plotting a slope
  • Adsorption
    • about / Theory-driven nonlinear regression
  • adsorption dataset
    • about / The adsorption and body measures datasets
    • URL / The adsorption and body measures datasets
  • agrep function / String processing and pattern matching
  • Akaike information criterion (AIC) value / The propagate package
  • amelia command / The Amelia package
  • Amelia package
    • about / The Amelia package
    • estimates, obtaining from multiply imputed datasets / Getting estimates from multiply imputed datasets
  • Analysis of variance (Anova)
    • about / Analysis of variance
  • anova() function / Analysis of variance
  • aov() function / Analysis of variance
  • apply() function / The apply() function
  • array() function / Multidimensional arrays
  • atomic vectors
    • about / Atomic vectors
    • operations / Operations on vectors
  • attributes / Attributes
  • Augmented Dickey-Fuller (ADF) / Unit...
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83
Tech Concepts
36
Programming languages
73
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