By William N. Venables, David M. Smith

ISBN-10: 3900051127

ISBN-13: 9783900051129

This educational guide offers a entire advent to R, a software program package deal for statistical computing and images. R helps a variety of statistical options and is definitely extensible through user-defined services. certainly one of R's strengths is the benefit with which publication-quality plots should be produced in a wide selection of codecs. this can be a published variation of the educational documentation from the R distribution, with extra examples, notes and corrections. it really is in line with R model 2.9.0, published April 2009. R is loose software program, allotted less than the phrases of the GNU basic Public License (GPL). it may be used with GNU/Linux, Unix and Microsoft home windows. the entire cash raised from the sale of this booklet helps the improvement of loose software program and documentation.

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**Example text**

The result of svd(M) is actually a list of three components named d, u and v, with evident meanings. 2 Even better would be to form a matrix square root B with A = BB T and find the squared length of the solution of By = x, perhaps using the Cholesky or eigendecomposition of A. Chapter 5: Arrays and matrices 25 If M is in fact square, then, it is not hard to see that > absdetM <- prod(svd(M)$d) calculates the absolute value of the determinant of M. If this calculation were needed often with a variety of matrices it could be defined as an R function > absdet <- function(M) prod(svd(M)$d) after which we could use absdet() as just another R function.

This is called lexical scope. First we define a function called cube. cube <- function(n) { sq <- function() n*n n*sq() } The variable n in the function sq is not an argument to that function. Therefore it is a free variable and the scoping rules must be used to ascertain the value that is to be associated with it. Under static scope (S-Plus) the value is that associated with a global variable named n. Under lexical scope (R) it is the parameter to the function cube since that is the active binding for the variable n at the time the function sq was defined.

Although still useful in some contexts, it would now generally be replaced by the statistical models features, as will be discussed in Chapter 11 [Statistical models in R], page 54. 8 Forming partitioned matrices, cbind() and rbind() As we have already seen informally, matrices can be built up from other vectors and matrices by the functions cbind() and rbind(). Roughly cbind() forms matrices by binding together matrices horizontally, or column-wise, and rbind() vertically, or row-wise. ) Chapter 5: Arrays and matrices 26 the arguments to cbind() must be either vectors of any length, or matrices with the same column size, that is the same number of rows.