Text Analysis with R for Students of Literature by Matthew L. Jockers, published by Springer.
This is a well written book on the topic of Text Analysis. There is enough information to give you a good start using R. Followed by easy to understand details about text analysis.
Covered in Chapter 6 type token ratio, TTR.
Chapter 7 hapex legomena, words that appear in frequency.
Chapter 8, KWIC Key word context. Including how to make a corpus.
Chapter 11, covers clustering. Chapter 12, classification Shows how to do crosstabs with xtabs function. Also SVM support Vector Machine.
Chapter 13 covers topic modeling.
This is a good book to have if you are doing text analysis.
Solving Differential Equations in R
by Karline Soetaert, Jeff Cash and Francesca Mazzia
Published by Springer Press
The books’ package on CRAN is diffEq.
I happily read through this book on a Sunday afternoon. It is a straight forward book to use if you already understand differential equations and can program in R. If either topic is new to you , learn them first then tackle this book.
It is much easier to code Euler’s and Newton’s method in R than the C and FORTRAN the code I originally used for these methods.
My favorite bit of code is the Elastica Problem in Chapter 11. The problem is a system of five differential equations describing an elastica in the x,y plane. Uses package bvpSolve. The package for solving boundary value problems.
Figure 2.4 page 37 is a nice chart of the main Families of IVP, Initial Value Problems solutions.
This book gives you the tools you need to solve differential equations in R.