Nothing
##
## PURPOSE: Best linear approximation
## (theoretical least squares)
##
## AUTHOR: Arnost Komarek (LaTeX: Arno\v{s}t Kom\'arek)
## arnost.komarek[AT]mff.cuni.cz
##
## CREATED: 19/11/2007
## 15/03/2017 .C call uses registered routines
##
## FUNCTIONS: BLA
##
## ======================================================================
## *************************************************************
## BLA
## *************************************************************
BLA <- function(mean=c(0, 0), Sigma=diag(2))
{
thispackage <- "mixAK"
p <- length(mean)
LTp.1 <- ((p-1)*p)/2
if (p <= 1) stop("mean must be of length >= 2")
if (is.null(dim(Sigma))) stop("Sigma must be a matrix")
if (p != nrow(Sigma) | p != ncol(Sigma)) stop("mean and Sigma are not consistent")
Sigma <- Sigma[lower.tri(Sigma, diag=TRUE)]
RES <- .C(C_BLA, beta =double(p*p),
sigmaR2=double(p),
L =double(LTp.1),
err =integer(1),
mu =as.double(mean),
Sigma =as.double(Sigma),
p =as.integer(p),
PACKAGE=thispackage)
if (RES$err) stop("Sigma is singular")
beta <- matrix(RES$beta, nrow=p, byrow=TRUE)
rownames(beta) <- names(RES$sigmaR2) <- paste("x", 1:p, sep="")
colnames(beta) <- paste("beta", 0:(p-1), sep="")
RET <- list(beta=beta,
sigmaR2=RES$sigmaR2)
return(RET)
}
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