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###{{{ print.lvm
##' @export
`print.lvm` <-
function(x, ..., print.transform=TRUE,print.exogenous=TRUE) {
res <- NULL
myhooks <- gethook("print.hooks")
for (f in myhooks) {
res <- do.call(f, list(x=x, ...))
}
if (is.null(res)) {
k <- length(vars(x))
L <- rep(FALSE, k); names(L) <- vars(x); L[latent(x)] <- TRUE
cat("Latent Variable Model\n") ##;" \n\twith: ", k, " variables.\n", sep="");
if (k==0) {
cat("\nEmpty\n")
return()
}
ff <- formula(x, char=TRUE, all=TRUE)
R <- Rx <- Rt <- c()
exo <- exogenous(x)
for (f in ff) {
oneline <- as.character(f);
y <- strsplit(f, "~")[[1]][1]
y <- trim(y)
{
col1 <- as.character(oneline)
D <- attributes(distribution(x)[[y]])$family
Tr <- x$attributes$transform[[y]]
col2 <- tryCatch(x$attributes$type[[y]], error=function(...) NULL)
if (is.null(col2) || is.na(col2)) {
if (!is.na(x$covfix[y, y]) && x$covfix[y, y]==0L) {
col2 <- "deterministic"
} else {
col2 <- "gaussian"
}
}
if (!is.null(Tr)){
col1 <- paste0(y, " ~ ", paste0(Tr$x, collapse="+"), sep="")
Rt <- rbind(Rt, c(col1, ""))
}
if (!is.null(D$family)) {
col2 <- paste0(D$family)
}
if (!is.null(D$link)) col2 <- paste0(col2, "(", D$link, ")")
if (!is.null(D$par)) col2 <- paste0(col2, "(", paste(D$par, collapse=","), ")")
if (is.list(distribution(x)[[y]]) && is.vector(distribution(x)[[y]][[1]])) col2 <- "fixed"
if (L[y]) col2 <- paste0(col2, ", latent")
if (y%in%exo) {
Rx <- rbind(Rx,c(col1, col2))
} else {
if (is.null(Tr)) {
R <- rbind(R,c(col1, col2))
}
}
}
}
if (length(R)>0) {
rownames(R) <- paste(" ", R[, 1], " "); colnames(R) <- rep("", ncol(R))
print(R[, 2, drop=FALSE], quote=FALSE, ...)
}
if (print.exogenous && length(Rx)>0) {
cat("\nExogenous variables:")
rownames(Rx) <- paste(" ", gsub("~ 1", "", Rx[, 1]), " "); colnames(Rx) <- rep("", ncol(Rx))
print(Rx[, 2, drop=FALSE], quote=FALSE, ...)
}
if (print.transform && length(Rt)>0) {
cat("\nTransformations:")
rownames(Rt) <- paste(" ", gsub("~ 1", "", Rt[,1]), " "); colnames(Rt) <- rep("", ncol(Rt))
print(Rt[,2,drop=FALSE],quote=FALSE, ...)
}
}
cat("\n")
invisible(x)
}
###}}} print.lvm
###{{{ print.lvmfit
##' @export
`print.lvmfit` <-
function(x,type=2,labels=FALSE,...) {
print(CoefMat(x,labels=labels,type=type,...),quote=FALSE,right=TRUE)
minSV <- attr(vcov(x),"minSV")
if (!is.null(minSV) && minSV<1e-12) {
warning("Small singular value: ", format(minSV))
}
pseudo <- attr(vcov(x),"pseudo")
if (!is.null(pseudo) && pseudo) warning("Singular covariance matrix. Pseudo-inverse used.")
invisible(x)
}
###}}} print.lvmfit
###{{{ print.lvmfit.randomslope
##' @export
print.lvmfit.randomslope <- function(x,labels=FALSE,type=2,...) {
print(CoefMat(x,labels=labels,type=type,...),quote=FALSE,right=TRUE)
invisible(x)
}
###}}}
###{{{ print.multigroupfit
##' @export
print.multigroupfit <- function(x,groups=NULL,...) {
if (is.null(groups)) {
if (x$model$missing) {
modelclass <- attributes(x$model0)$modelclass
nmis <- attributes(x$model0)$nmis
orggroup <- unique(modelclass)
groupn <- unlist(lapply(orggroup,function(i) sum(modelclass==i)))
cumsumgroup <- cumsum(c(0,groupn))
groups <- unlist(lapply(orggroup,function(i)
which.min(nmis[which(modelclass==i)])+cumsumgroup[i])) ## groups with max. number of variables
for (i in seq_len(length(groups))) {
if (nmis[groups[i]]>0) warning("No complete cases in group ",i,". Showing results of group with max number of variables. All coefficients can be extracted with 'coef'. All missing pattern groups belonging to this sub-model can be extracted by calling: coef(..., groups=c(",paste(which(modelclass==i),collapse=","),"))")
}
if (!is.null(x$model$mnameses))
x$model$names <- x$model$mnames
} else {
groups <- seq_len(length(x$model$lvm))
}
}
res <- coef(x,type=2,groups=groups,...)
counter <- 0
dots <- list(...)
dots$groups <- groups
type <- if (is.null(dots$type)) {
dots$type <- 2
## dots$type <- ifelse("lvmfit.randomslope"%in%class(x),2,9)
}
myargs <- c(list(x=x), dots)
myargs$groups <- groups
CC <- do.call("CoefMat.multigroupfit",myargs)
for (cc in res) {
counter <- counter+1
cat(rep("_",52),"\n",sep="")
cat("Group ", counter, sep="")
myname <- x$model$names[counter]
if (!is.null(myname) && !is.na(myname))
cat(": ",myname,sep="")
if (!x$model$missing) cat(" (n=",nrow(Model(x)$data[[groups[counter]]]), ")", sep="")
cat("\n")
print(CC[[counter]],quote=FALSE,right=TRUE)
}
cat("\n")
invisible(x)
}
###}}} print.multigroupfit
###{{{ print.multigroup
##' @export
print.multigroup <- function(x,...) {
cat("\n")
cat("Number of groups:", x$ngroup, "\n")
cat("Number of free parameters (not counting mean-parameters):", x$npar,"\n")
## cat("Parameter-vector:", unlist(x$parlist), "\n\n")
cat("Number of free mean parameters:", length(grep("m",x$mean)),"\n")
## cat("Mean-vector:", x$mean, "\n\n")
invisible(x)
}
###}}} print.multigroup
###{{{ printmany
printmany <- function(A,B,nspace=1,name1=NULL,name2=NULL,digits=3,rownames=NULL,emptystr=" ",bothrows=!is.table(A),right=TRUE,print=TRUE,...) {
A <- format(A, digits=digits, right=right, ...)
B <- format(B, digits=digits, right=right, ...)
nA <- nrow(A); nB <- nrow(B)
if (nrow(A)<nrow(B)) {
A <- rbind(A, matrix("", nrow=nB-nA, ncol=ncol(A)))
}
if (nrow(B)<nrow(A)) {
B <- rbind(B, rep("", nrow=nA-nB, ncol=ncol(B)))
}
if (!is.null(rownames) & length(rownames)==nrow(A))
rownames(A) <- rownames(B) <- rownames
res <- cbind(A, matrix("", nrow=nrow(A), ncol=nspace));
dnn <- dimnames(A)
dnn[[2]] <- c(dnn[[2]],rep(emptystr,nspace))
dimnames(res) <- dnn
##dimnames(res)[[2]] <- c(dimnames(res)[[2]],rep(emptystr,nspace))
if (!is.null(name1)) {
oldname <- colnames(res)
res <- cbind(rep("",nrow(res)), rownames(res), res);
cres <- name1
if (!is.null(rownames(res))) cres <- c(cres,"")
colnames(res) <- c(cres,oldname)
rownames(res) <- rep("",nrow(res))
}
if (!is.null(name2)) {
oldname <- colnames(res)
res <- cbind(res,rep("",nrow(res))); colnames(res) <- c(oldname,name2)
}
if (!identical(rownames(A),rownames(B)) & bothrows)
res <- cbind(res, rownames(B))
res <- cbind(res, B)
if (is.null(name2)) {
dnn[[2]] <- c(dnn[[2]],dimnames(B)[[2]])
dimnames(res) <- dnn
}
if (print) print(res, quote=FALSE, right=right, ...)
invisible(res)
}
###}}} printmany
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