Computational Methods for Numerical Analysis with R
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A01=II Howard
A01=James P Howard
Adams Bashforth Method
advanced numerical techniques in R
algorithm implementation
applied mathematics
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Author_II Howard
Author_James P Howard
Bilinear Interpolation
Category=PBKS
Category=PBT
Category=UB
Cubic Spline
Data Frame
differential equations
Double Precision
Elementary Row Operations
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Euler Method
Finite Differences Method
Fourth Order Runge Kutta Method
Global Truncation Error
Golden Section Search
Gradient Descent
II
integration
interpolation
James P Howard
linear algebra
Local Truncation Error
LU Decomposition
matrix computation
Midpoint Method
Midpoint Rule
Newton Raphson Method
Numeric Data Type
numerical modeling
optimization
Ordinary Differential Equations
Piecewise Linear Interpolation
Polynomial Interpolation
quantitative analysis
Reduced Row Echelon Form
Row Echelon Form
Runge Kutta Methods
scientific computing
Simulated Annealing
Product details
- ISBN 9780367657918
- Weight: 540g
- Dimensions: 156 x 234mm
- Publication Date: 30 Sep 2020
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Paperback
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Computational Methods for Numerical Analysis with R is an overview of traditional numerical analysis topics presented using R. This guide shows how common functions from linear algebra, interpolation, numerical integration, optimization, and differential equations can be implemented in pure R code. Every algorithm described is given with a complete function implementation in R, along with examples to demonstrate the function and its use.
Computational Methods for Numerical Analysis with R is intended for those who already know R, but are interested in learning more about how the underlying algorithms work. As such, it is suitable for statisticians, economists, and engineers, and others with a computational and numerical background.
James P Howard, II
