Nothing
##-----------------------------------------------------------------------
## This function calculates the cost matrix for a homoscedastic model
## G[k,i] is the sum of squared residuals of a segment from i to (i+k-1)
##-----------------------------------------------------------------------
costMatrix = function(x, maxk) {
if(!is.numeric(x)||!(is.vector(x)||is.matrix(x)))
stop("'x' must be a numeric vector or matrix.")
if(is.vector(x)) {
r = x
q = x*x
d = 1
} else {
r = rowSums(x)
q = rowSums(x*x)
d = ncol(x)
}
n = length(r)
if(!is.numeric(maxk)||(length(maxk)!=1)||(maxk<=1)||(maxk>n))
stop(sprintf("'maxk' must be a single number between 2 and the number of rows of 'x': %d.", n))
## see inst/doc/costMatrix.tex (.pdf) for explanation of the algebra
cr = cumsum(r)
cq = cumsum(q)
G = matrix(as.numeric(NA), nrow=maxk, ncol=n)
k = 1:maxk
G[, 1] = cq[k] - cr[k]*cr[k]/(k*d)
m = if(n==maxk) (maxk-1) else (maxk)
for(k in seq_len(m)) {
i = 1:(n-k)
j = 2:(n-k+1)
cqk = cq[i+k]-cq[i]
crk = cr[i+k]-cr[i]
G[k,j] = cqk - crk*crk/(k*d)
}
return(G)
}
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