# R and MATLAB

© 2015 – Chapman and Hall/CRC

233 pages | 10 B/W Illus.

Hardback: 9781466568389
pub: 2015-06-02
US Dollars\$69.95
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The First Book to Explain How a User of R or MATLAB Can Benefit from the Other

In today’s increasingly interdisciplinary world, R and MATLAB® users from different backgrounds must often work together and share code. R and MATLAB® is designed for users who already know R or MATLAB and now need to learn the other platform. The book makes the transition from one platform to the other as quick and painless as possible.

Enables R and MATLAB Users to Easily Collaborate and Share Code

The author covers essential tasks, such as working with matrices and vectors, writing functions and other programming concepts, graphics, numerical computing, and file input/output. He highlights important differences between the two platforms and explores common mistakes that are easy to make when transitioning from one platform to the other.

Installing and Running R and MATLAB

Obtaining and installing

Commands for getting help

Demos

Quitting

Getting Started: Variables and Basic Computations

Variable names

Assignment statements

Basic computations

Formatting of output

Other computations

Complex numbers

Strange variable names in R

Data types

Matrices and Vectors

Overview

Creating vectors

Working with vectors

Creating matrices

Working with matrices

Reshaping matrices, and higher-dimensional arrays

Sparse matrices

Names with vectors and matrices/arrays

Miscellaneous

Matrix/Vector Calculations and Functions

Applying a function to rows or columns of a matrix

Applying a function to all elements of a matrix

Linear algebra calculations with vectors and matrices

Statistical calculations

Vectorized logical tests

Other calculations

Lists and Cell Arrays

Creating lists and cell arrays

Using lists and cell arrays

Applying functions to all elements of lists and cell arrays

Converting other data types to lists and cell arrays

Converting lists and cell arrays to other data types

Flow Control

Conditional ("if") statements

"If/else" statements

"for" loops

"while" loops

Breaking out of loops

"switch" statements

"ifelse" statements in R

Running Code from Files: Scripts

Current working directory

The MATLAB search path

Executing code from a file

Creating a new script document in the editor

Executing code from the editor window

Summary of differences

R

MATLAB

Summary of main differences

Probability and Random Numbers

Basic random values, permutations, and samples

Random number seed

Random variates from probability distributions

PDFs, CDFs, and inverse CDFs

Graphics

Creating, selecting, and closing figure windows

Basic 2-D scatterplots

Axis ranges

Logarithmic axis scales

Background grid

Plotting multiple data sets simultaneously

Axis labels and figure titles

Greek letters and mathematical symbols

Arrows

Figure legends

Two y axes

Plotting functions

Image plots and contours

Colormaps

3-D plotting

Multiple subplots in one figure

Saving figures

Other types of plots

Numerical Computing

Root-finding

Univariate optimization

Multivariate optimization

Numerical integration

Curve fitting

Differential equations

File Input and Output

Opening files

Reading numeric data with a different comment character

Reading numbers from a file where different lines have varying numbers of values

Reading the raw character data in, a line at a time

Writing a table of numbers

Writing a set of strings

Images

URLs

Excel files

Miscellaneous

Working with variables

Character strings

Recording a copy of commands and output

Date calculations

Miscellaneous

Debugging

Startup and shutdown sequences

Object-oriented programming

Other interfaces

Efficiency/performance

Calling C

R

MATLAB

Bibliography

Index of R commands, variables, and symbols

Index of MATLAB commands, variables, and symbols

David E. Hiebeler is an associate professor in the Department of Mathematics & Statistics at the University of Maine. He earned a PhD in applied mathematics from Cornell University. His research involves mathematical and computational stochastic spatial models in population ecology and epidemiology.