Nothing
samonGenIM <- function(mat,
Npart = 10,
InitialSigmaH = 1.0,
HighSigmaH = 2.0,
InitialSigmaF = 1.0,
HighSigmaF = 2.0,
inmodel = inmodel,
NSamples = 0,
seed0 = 1,
seed1 = 1,
MaxIter = 25,
FAconvg = 1E-7,
FRconvg = 1E-7,
SAconvg = 1E-7
)
{
nt <- ncol(mat)
n0 <- nrow(mat)
# some sizes
nmodel <- 6
nfills <- 1
FMat <- matrix( 0, n0 * nfills, nt + 2, )
LEstsM <- matrix( 0, nt * nfills, nmodel + 7)
ModelsM <- matrix( 0, nt * nfills, nmodel )
HM <- matrix( 0, nrow = nfills, ncol = 6 )
FM <- matrix( 0, nrow = nfills, ncol = 6 )
Sample <- matrix( 0, nrow = NSamples, ncol = nt+1 )
mat <- as.matrix(mat)
fout <- .C("samon_genIM",
n0 = as.integer ( n0 ),
nt = as.integer ( nt ),
mat = as.double ( as.vector( mat ) ),
nmodel = as.integer ( nmodel ),
inmodel = as.integer ( as.vector( inmodel ) ),
FMat = as.double ( as.vector( FMat ) ),
LEstsM = as.double ( as.vector( LEstsM ) ),
ModelsM = as.integer ( as.vector( ModelsM ) ),
HM = as.double ( as.vector( HM ) ),
FM = as.double ( as.vector( FM ) ),
seed0 = as.integer ( seed0 ),
seed1 = as.integer ( seed1 ),
InitialSigmaH = as.double ( InitialSigmaH ),
HighSigmaH = as.double ( HighSigmaH ),
InitialSigmaF = as.double ( InitialSigmaF ),
HighSigmaF = as.double ( HighSigmaF ),
Npart = as.integer ( Npart ),
NSamples = as.integer ( NSamples ),
MaxIter = as.integer ( MaxIter ),
FAconvg = as.double ( FAconvg ),
FRconvg = as.double ( FRconvg ),
SAconvg = as.double ( SAconvg ),
NFills = as.integer ( nfills ),
Sample = as.double ( as.vector( Sample ) ),
NAOK=TRUE
)
hnames <- c("Sample", "Type", "Convergence", "Iterations", "SigmaH", "lossH" )
fnames <- c("Sample", "Type", "Convergence", "Iterations", "SigmaF", "lossF" )
anames <- c("Sample", "Type", "alpha", "AEst", "AVar", "IFEst", "IFVar" )
IFinamesMB <- c("Sample", "alpha", "Obsno", "AEst", "IFEst" )
# always done
if ( TRUE ) {
fout$HM <- matrix( fout$HM, nrow = nfills, ncol = 6, byrow = TRUE )
fout$FM <- matrix( fout$FM, nrow = nfills, ncol = 6, byrow = TRUE )
colnames(fout$HM) <- hnames
colnames(fout$FM) <- fnames
fout$inmodel <- matrix(fout$inmodel, nrow= nt, ncol = nmodel, byrow = FALSE )
fout$FMat <- matrix(fout$FMat, nrow= n0 * nfills, ncol = nt + 2, byrow = TRUE )
fout$LEstsM <- matrix(fout$LEstsM, nrow= nt * nfills, ncol = nmodel+7, byrow = TRUE )
fout$ModelsM <- matrix(fout$ModelsM, nrow= nt * nfills, ncol = nmodel, byrow = TRUE )
}
if ( NSamples > 0 ) {
fout$Sample <- matrix(fout$Sample, nrow= NSamples, ncol = nt+1, byrow = TRUE )
## change NaN to NA
fout$Sample[ is.nan(fout$Sample) ] <- NA
}
fout$mat <- matrix(fout$mat, nrow= n0,ncol = nt, byrow=FALSE )
return(fout)
}
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