spam (version 2.5-1)

spam: Sparse Matrix Class

Description

This group of functions evaluates and coerces changes in class structure.

Usage

spam(x, nrow = 1, ncol = 1, eps = getOption("spam.eps"))
as.spam(x, eps = getOption("spam.eps"))
is.spam(x)

Arguments

x

is a matrix (of either dense or sparse form), a list, vector object or a distance object

nrow

number of rows of matrix

ncol

number of columns of matrix

eps

A tolerance parameter: elements of x such that abs(x) < eps set to zero. Defaults to eps = getOption("spam.eps")

Value

A valid spam object. is.spam returns TRUE if x is a spam object.

Details

The functions spam and as.spam act like matrix and as.matrix to coerce an object to a sparse matrix object of class spam.

If x is a list, it should contain either two or three elements. In case of the former, the list should contain a n by two matrix of indicies (called ind) and the values. In case of the latter, the list should contain three vectors containing the row, column indices (called i and j) and the values. In both cases partial matching is done. In case there are several triplets with the same i, j, the values are added.

eps should be at least as large as .Machine$double.eps.

If getOption("spam.force64") is TRUE, a 64-bit spam matrix is returned in any case. If FALSE, a 32-bit matrix is returned when possible.

References

Reinhard Furrer, Stephan R. Sain (2010). "spam: A Sparse Matrix R Package with Emphasis on MCMC Methods for Gaussian Markov Random Fields.", Journal of Statistical Software, 36(10), 1-25, http://www.jstatsoft.org/v36/i10/.

See Also

SPAM for a general overview of the package; spam_random to create matrices with a random sparsity pattern; cleanup to purge a sparse matrix; spam.options for details about the safemode flag; read.MM and foreign to create spam matrices from MatrixMarket files and from certain Matrix or SparseM formats.

Examples

# NOT RUN {
# old message, do not loop, when you create a large sparse matrix
set.seed(13)
nz <- 128
ln <- nz^2
smat <- spam(0,ln,ln)
is <- sample(ln,nz)
js <- sample(ln,nz)
system.time(for (i in 1:nz) smat[is[i], js[i]] <- i)
system.time(smat[cbind(is,js)] <- 1:nz)

getClass("spam")


options(spam.NAOK=TRUE)
as.spam(c(1, NA))
# }