# # # # # # # # # # # # #
# makeArgs.rma #
# # # # # # # # # # # # #
makeArgs.default = utils::getFromNamespace("makeArgs.default", "MuMIn")
makeArgs = utils::getFromNamespace("makeArgs", "MuMIn")
#' @export
#' @method makeArgs rma
makeArgs.rma = function(obj, termNames, comb, opt, ...) {
return <- makeArgs.default(obj, termNames, comb, opt)
names(return)[1L] = "mods"
return
}
# # # # # # # # # # # # #
# coefTable.rma #
# # # # # # # # # # # # #
.makeCoefTable = utils::getFromNamespace(".makeCoefTable", "MuMIn")
#' @export
#' @method coefTable rma
coefTable.rma = function(model, ...) {
.makeCoefTable(model$b, model$se, coefNames = rownames(model$b))
}
#' @importFrom stats nobs formula terms
dredge2 = function(global.model, beta = c("none", "sd", "partial.sd"),
evaluate = TRUE, rank = "AICc", fixed = NULL, m.lim = NULL,
m.min, m.max, subset, trace = FALSE, varying, extra, ct.args = NULL,
...)
{
# Uses function code from MuMIn
# Uses code adapted from MuMIn (GPLv2 License)
# Copyright (C) 2019 Kamil Bartón
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
asChar <- utils::getFromNamespace("asChar", "MuMIn")
.getLik <- utils::getFromNamespace(".getLik", "MuMIn")
isGEE <- utils::getFromNamespace("isGEE", "MuMIn")
.getRank <- utils::getFromNamespace(".getRank", "MuMIn")
.checkNaAction <- utils::getFromNamespace(".checkNaAction", "MuMIn")
fixCoefNames <- utils::getFromNamespace("fixCoefNames", "MuMIn")
.isREMLFit <- utils::getFromNamespace(".isREMLFit", "MuMIn")
abbreviateTerms <- utils::getFromNamespace("abbreviateTerms", "MuMIn")
AICc <- utils::getFromNamespace("AICc", "MuMIn")
aicloglik_glm_fit <- utils::getFromNamespace("aicloglik_glm_fit", "MuMIn")
applyrns <- utils::getFromNamespace("applyrns", "MuMIn")
arm.glm <- utils::getFromNamespace("arm.glm", "MuMIn")
armWeights <- utils::getFromNamespace("armWeights", "MuMIn")
beta.weights <- utils::getFromNamespace("beta.weights", "MuMIn")
BGWeights <- utils::getFromNamespace("BGWeights", "MuMIn")
CAICF <- utils::getFromNamespace("CAICF", "MuMIn")
cbindDataFrameList <- utils::getFromNamespace("cbindDataFrameList", "MuMIn")
checkIsModelDataIdentical <- utils::getFromNamespace("checkIsModelDataIdentical", "MuMIn")
clusterVExport <- utils::getFromNamespace("clusterVExport", "MuMIn")
coef.averaging <- utils::getFromNamespace("coef.averaging", "MuMIn")
coef.geese <- utils::getFromNamespace("coef.geese", "MuMIn")
coef.model.selection <- utils::getFromNamespace("coef.model.selection", "MuMIn")
coef.wgee <- utils::getFromNamespace("coef.wgee", "MuMIn")
coef.yagsResult <- utils::getFromNamespace("coef.yagsResult", "MuMIn")
prettyEnumStr <- utils::getFromNamespace("prettyEnumStr", "MuMIn")
formula_margin_check <- utils::getFromNamespace("formula_margin_check", "MuMIn")
matchCoef <- utils::getFromNamespace("matchCoef", "MuMIn")
cry <- utils::getFromNamespace("cry", "MuMIn")
subst <- utils::getFromNamespace("subst", "MuMIn")
updateDeps <- utils::getFromNamespace("updateDeps", "MuMIn")
.DebugPrint <- utils::getFromNamespace(".DebugPrint", "MuMIn")
exprapply0 <- utils::getFromNamespace("exprapply0", "MuMIn")
exprApply <- utils::getFromNamespace("exprApply", "MuMIn")
.subst.names.for.items <- utils::getFromNamespace(".subst.names.for.items", "MuMIn")
evalExprInEnv <- utils::getFromNamespace("evalExprInEnv", "MuMIn")
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
trace <- min(as.integer(trace), 2L)
strbeta <- betaMode <- NULL
eval(expression({
if (is.logical(beta) && beta) {
betaMode <- as.integer(beta)
strbeta <- if (beta)
"sd"
else "none"
}
else if (is.character(beta)) {
strbeta <- match.arg(beta)
beta <- strbeta != "none"
betaMode <- (strbeta != "none") + (strbeta == "partial.sd")
}
else {
betaMode <- 0L
strbeta <- "none"
}
}))
gmEnv <- parent.frame()
gmNobs <- nobs(global.model)
gmCall <- get_call(global.model)
if (is.null(gmCall)) {
gmCall <- substitute(global.model)
if (!is.call(gmCall)) {
stop("need a 'global.model' with a call component. Consider using ",
if (inherits(global.model, c("gamm", "gamm4")))
"'uGamm'"
else "'updateable'")
}
if (!is.function(eval.parent(gmCall[[1L]])))
cry(, "could not find function '%s'", asChar(gmCall[[1L]]))
}
else {
isDotted <- grep("^\\.\\.", sapply(as.list(gmCall), asChar))
if (length(isDotted) != 0L) {
if (is.name(substitute(global.model))) {
cry(, "call stored in 'global.model' contains dotted names and cannot be updated. \n Consider using 'updateable' on the modelling function")
}
else gmCall[isDotted] <- substitute(global.model)[names(gmCall[isDotted])]
}
if (inherits(global.model, "mark") && gmCall[[1L]] ==
"make.mark.model") {
gmCall <- call("run.mark.model", model = gmCall,
invisible = TRUE)
}
}
thisCall <- sys.call()
exprApply(gmCall[["data"]], NA, function(expr) {
if (is.symbol(expr[[1L]]) && all(expr[[1L]] != c("@",
"$")))
cry(thisCall, "'global.model' uses \"data\" that is a function value: use a variable instead")
})
lik <- .getLik(global.model)
logLik <- lik$logLik
rank.custom <- !missing(rank)
if (!rank.custom && lik$name == "qLik") {
rank <- "QIC"
cry(, "using 'QIC' instead of 'AICc'", warn = TRUE)
}
rankArgs <- list(...)
if (any(badargs <- names(rankArgs) == "marg.ex")) {
cry(, "argument \"marg.ex\" is defunct and has been ignored",
warn = TRUE)
rankArgs <- rankArgs[!badargs]
}
if (any(names(rankArgs) == "na.action"))
cry("RTFM", "argument \"na.action\" is inappropriate here",
warn = FALSE)
IC <- .getRank(rank, rankArgs)
if (any(badargs <- is.na(match(names(rankArgs), c(names(formals(get("rank",
environment(IC))))[-1L], names(formals()))))))
cry("RTFM", ngettext(sum(badargs), "argument %s is not a name of formal argument of %s",
"arguments %s are not names of formal arguments of %s"),
prettyEnumStr(names(rankArgs[badargs])), "'dredge' or 'rank'",
warn = TRUE)
ICName <- as.character(attr(IC, "call")[[1L]])
if (length(tryCatch(IC(global.model), error = function(e) {
stop(simpleError(conditionMessage(e), subst(attr(IC,
"call"), x = as.name("global.model"))))
})) != 1L) {
cry(, "result of '%s' is not of length 1", asChar(attr(IC,
"call")))
}
allTerms <- allTerms0 <- getAllTerms(global.model, intercept = TRUE,
data = eval(gmCall$data, envir = gmEnv))
interceptLabel <- attr(allTerms, "interceptLabel")
if (is.null(interceptLabel))
interceptLabel <- "(Intercept)"
nIntercepts <- sum(attr(allTerms, "intercept"))
if (!(gmNaAction <- .checkNaAction(cl = gmCall, what = "'global.model'")))
cry(, attr(gmNaAction, "message"))
if (names(gmCall)[2L] == "")
gmCall <- match.call(gmCall, definition = eval.parent(gmCall[[1L]]),
expand.dots = TRUE)
gmCoefNames <- names(coeffs(global.model))
if (any(dup <- duplicated(gmCoefNames)))
cry(, "model cannot have duplicated coefficient names: ",
prettyEnumStr(gmCoefNames[dup]))
gmCoefNames <- fixCoefNames(gmCoefNames)
nVars <- length(allTerms)
if (isTRUE(rankArgs$REML) || (isTRUE(.isREMLFit(global.model)) &&
is.null(rankArgs$REML)))
cry(, "comparing models fitted by REML", warn = TRUE)
if ((betaMode != 0L) && is.null(tryCatch(std.coef(global.model,
betaMode == 2L), error = return_null, warning = return_null))) {
cry(, "do not know how to standardize coefficients of '%s', argument 'beta' ignored",
class(global.model)[1L], warn = TRUE)
betaMode <- 0L
strbeta <- "none"
}
if (nomlim <- is.null(m.lim))
m.lim <- c(0, NA)
if (!missing(m.max) || !missing(m.min)) {
warning("arguments 'm.min' and 'm.max' are deprecated, use 'm.lim' instead")
if (!nomlim)
stop("cannot use both 'm.lim' and 'm.min' or 'm.max'")
if (!missing(m.min))
m.lim[1L] <- m.min[1L]
if (!missing(m.max))
m.lim[2L] <- m.max[1L]
}
if (!is.numeric(m.lim) || length(m.lim) != 2L || any(m.lim <
0, na.rm = TRUE))
stop("invalid 'm.lim' value")
m.lim[2L] <- if (!is.finite(m.lim[2L]))
(nVars - nIntercepts)
else min(nVars - nIntercepts, m.lim[2L])
if (!is.finite(m.lim[1L]))
m.lim[1L] <- 0
m.min <- m.lim[1L]
m.max <- m.lim[2L]
if (!is.null(fixed)) {
if (inherits(fixed, "formula")) {
if (fixed[[1L]] != "~" || length(fixed) != 2L)
cry(, "'fixed' should be a one-sided formula",
warn = TRUE)
fixed <- as.vector(getAllTerms(fixed))
}
else if (identical(fixed, TRUE)) {
fixed <- as.vector(allTerms[!(allTerms %in% interceptLabel)])
}
else if (!is.character(fixed)) {
cry(, paste("'fixed' should be either a character vector with",
" names of variables or a one-sided formula"))
}
if (!all(i <- (fixed %in% allTerms))) {
cry(, "some terms in 'fixed' do not exist in 'global.model': %s",
prettyEnumStr(fixed[!i]), warn = TRUE)
fixed <- fixed[i]
}
}
deps <- attr(allTerms0, "deps")
fixed <- union(fixed, rownames(deps)[rowSums(deps, na.rm = TRUE) ==
ncol(deps)])
fixed <- c(fixed, allTerms[allTerms %in% interceptLabel])
nFixed <- length(fixed)
if (nFixed != 0L)
message(sprintf(ngettext(nFixed, "Fixed term is %s",
"Fixed terms are %s"), prettyEnumStr(fixed)))
termsOrder <- order(allTerms %in% fixed)
allTerms <- allTerms[termsOrder]
di <- match(allTerms, rownames(deps))
deps <- deps[di, di, drop = FALSE]
gmFormulaEnv <- environment(as.formula(formula(global.model),
env = gmEnv))
if (!missing(varying) && !is.null(varying)) {
nVarying <- length(varying)
varyingNames <- names(varying)
fvarying <- unlist(varying, recursive = FALSE, use.names = FALSE)
vlen <- vapply(varying, length, 1L)
nVariants <- prod(vlen)
variants <- as.matrix(expand.grid(split(seq_len(sum(vlen)),
rep(seq_len(nVarying), vlen))))
variantsFlat <- unlist(lapply(varying, .makeListNames),
recursive = FALSE, use.names = FALSE)
}
else {
variants <- varyingNames <- NULL
nVariants <- 1L
nVarying <- 0L
}
if (!missing(extra) && length(extra) != 0L) {
if (any(c("adjR^2", "R^2") %in% extra) && nVariants >
1L)
stop("\"R^2\" in 'extra' can be used only with no 'varying'")
extra <- eval(as.call(list(call("get", ".get.extras",
envir = call("asNamespace", .packageName), inherits = FALSE),
substitute(extra), r2nullfit = TRUE)), parent.frame())
if (any(c("adjR^2", "R^2") %in% names(extra))) {
nullfit_ <- null.fit(global.model, evaluate = TRUE,
envir = gmFormulaEnv)
}
applyExtras <- function(x) unlist(lapply(extra, function(f) f(x)))
extraResult <- applyExtras(global.model)
if (!is.numeric(extraResult))
cry(, "function in 'extra' returned non-numeric result")
nExtra <- length(extraResult)
extraNames <- names(extraResult)
}
else {
nExtra <- 0L
extraNames <- character(0L)
}
nov <- as.integer(nVars - nFixed)
ncomb <- (2L^nov) * nVariants
novMax <- log2(.Machine$integer.max%/%nVariants)
if (nov > novMax)
cry(, "number of non-fixed predictors [%d] exceeds the allowed maximum of %d (with %d variants)",
nov, novMax, nVariants)
resultChunkSize <- 25L
if (evaluate) {
rvNcol <- nVars + nVarying + 3L + nExtra
rval <- matrix(NA_real_, ncol = rvNcol, nrow = resultChunkSize)
coefTables <- vector(resultChunkSize, mode = "list")
}
if (missing(subset)) {
hasSubset <- 1L
}
else {
if (!tryCatch(is.language(subset) || is.matrix(subset),
error = function(e) FALSE))
subset <- substitute(subset)
if (is.matrix(subset)) {
dn <- dimnames(subset)
n <- length(allTerms)
if (is.null(dn) || any(sapply(dn, is.null))) {
di <- dim(subset)
if (any(di != n))
stop("unnamed 'subset' matrix does not have both dimensions",
" equal to number of terms in 'global.model': %d",
n)
dimnames(subset) <- list(allTerms, allTerms)
}
else {
if (!all(unique(unlist(dn)) %in% allTerms))
warning("at least some dimnames of 'subset' matrix do not ",
"match term names in 'global.model'")
subset0 <- subset
subset <- matrix(subset[match(allTerms, rownames(subset)),
match(allTerms, colnames(subset))], dimnames = list(allTerms,
allTerms), nrow = n, ncol = n)
nas <- is.na(subset)
lotri <- lower.tri(subset)
i <- lotri & nas & !t(nas)
subset[i] <- t(subset)[i]
subset[!lotri] <- NA
}
if (any(!is.na(subset[!lower.tri(subset)]))) {
warning("non-missing values exist outside the lower triangle of 'subset'")
subset[!lower.tri(subset)] <- NA
}
mode(subset) <- "logical"
hasSubset <- 2L
}
else {
if (inherits(subset, "formula")) {
if (subset[[1L]] != "~" || length(subset) !=
2L)
stop("'subset' formula should be one-sided")
subset <- subset[[2L]]
}
subset <- as.expression(subset)
ssValidNames <- c("comb", "*nvar*")
tmpTerms <- terms(reformulate(allTerms0[!(allTerms0 %in%
interceptLabel)]))
gloFactorTable <- t(attr(tmpTerms, "factors") !=
0)
offsetNames <- sapply(attr(tmpTerms, "variables")[attr(tmpTerms,
"offset") + 1L], asChar)
if (length(offsetNames) != 0L) {
gloFactorTable <- rbind(gloFactorTable, matrix(FALSE,
ncol = ncol(gloFactorTable), nrow = length(offsetNames),
dimnames = list(offsetNames, NULL)))
for (i in offsetNames) gloFactorTable[offsetNames,
offsetNames] <- TRUE
}
.DebugPrint(gloFactorTable)
rownames(gloFactorTable) <- allTerms0[!(allTerms0 %in%
interceptLabel)]
subsetExpr <- subset[[1L]]
subsetExpr <- exprapply0(subsetExpr, c("with", "."),
.subst.with, gloFactorTable, allTerms, as.name("comb"),
gmEnv)
subsetExpr <- exprapply0(subsetExpr, c("{", "Term"),
.subst.term)
tmp <- updateDeps(subsetExpr, deps)
subsetExpr <- tmp$expr
deps <- tmp$deps
subsetExpr <- exprapply0(subsetExpr, "dc", .subst.vars.for.args)
subsetExpr <- .subst.names.for.items(subsetExpr,
allTerms, "comb")
if (nVarying) {
ssValidNames <- c("cVar", "comb", "*nvar*")
subsetExpr <- exprapply0(subsetExpr, "V", .subst.v,
as.name("cVar"), varyingNames)
if (!all(all.vars(subsetExpr) %in% ssValidNames))
subsetExpr <- .subst.names.for.items(subsetExpr,
varyingNames, "cVar", fun = "[[")
}
ssVars <- all.vars(subsetExpr)
okVars <- ssVars %in% ssValidNames
if (!all(okVars))
stop("unrecognized names in 'subset' expression: ",
prettyEnumStr(ssVars[!okVars]))
ssEnv <- new.env(parent = parent.frame())
ssFunc <- setdiff(all.vars(subsetExpr, functions = TRUE),
ssVars)
if ("dc" %in% ssFunc)
assign("dc", .subset_dc, ssEnv)
hasSubset <- if (any(ssVars == "cVar"))
4L
else 3L
}
}
comb.sfx <- rep(TRUE, nFixed)
comb.seq <- if (nov != 0L)
seq_len(nov)
else 0L
k <- 0L
extraResult1 <- integer(0L)
calls <- vector(mode = "list", length = resultChunkSize)
ord <- integer(resultChunkSize)
argsOptions <- list(response = attr(allTerms0, "response"),
intercept = nIntercepts, interceptLabel = interceptLabel,
random = attr(allTerms0, "random"), gmCall = gmCall,
gmEnv = gmEnv, allTerms = allTerms0, gmCoefNames = gmCoefNames,
gmDataHead = if (!is.null(gmCall$data)) {
if (eval(call("is.data.frame", gmCall$data), gmEnv)) eval(call("head",
gmCall$data, 1L), gmEnv) else gmCall$data
} else NULL, gmFormulaEnv = gmFormulaEnv)
matchCoefCall <- as.call(c(alist(matchCoef, fit1, all.terms = allTerms,
beta = betaMode, allCoef = TRUE), ct.args))
retColIdx <- if (nVarying)
-nVars - seq_len(nVarying)
else TRUE
if (trace > 1L) {
progressBar <- if (.Platform$GUI == "Rgui") {
utils::winProgressBar(max = ncomb, title = "'dredge' in progress")
}
else utils::txtProgressBar(max = ncomb, style = 3L)
setProgressBar <- switch(class(progressBar), txtProgressBar = utils::setTxtProgressBar,
winProgressBar = utils::setWinProgressBar, function(...) {
})
on.exit(close(progressBar))
}
iComb <- -1L
while ((iComb <- iComb + 1L) < ncomb) {
varComb <- iComb%%nVariants
jComb <- (iComb - varComb)%/%nVariants
if (varComb == 0L) {
isok <- TRUE
comb <- c(as.logical(intToBits(jComb)[comb.seq]),
comb.sfx)
nvar <- sum(comb) - nIntercepts
if (nvar > m.max || nvar < m.min || !formula_margin_check(comb,
deps) || switch(hasSubset, FALSE, !all(subset[comb,
comb], na.rm = TRUE), !evalExprInEnv(subsetExpr,
env = ssEnv, enclos = parent.frame(), comb = comb,
`*nvar*` = nvar), FALSE)) {
isok <- FALSE
next
}
newArgs <- makeArgs.rma(global.model, allTerms[comb],
argsOptions)
if (!is.null(attr(newArgs, "problems"))) {
print.warnings(structure(vector(mode = "list",
length = length(attr(newArgs, "problems"))),
names = attr(newArgs, "problems")))
}
cl <- gmCall
cl[names(newArgs)] <- newArgs
}
if (!isok)
next
clVariant <- cl
if (nVarying) {
cvi <- variants[varComb + 1L, ]
if (hasSubset == 4L && !evalExprInEnv(subsetExpr,
env = ssEnv, enclos = parent.frame(), comb = comb,
`*nvar*` = nvar, cVar = variantsFlat[cvi]))
next
clVariant[varyingNames] <- fvarying[cvi]
}
if (trace == 1L) {
cat(iComb, ": ")
print(clVariant)
utils::flush.console()
}
else if (trace == 2L) {
setProgressBar(progressBar, value = iComb, title = sprintf("dredge: %d of %.0f subsets (%d total)",
k, (k/iComb) * ncomb, iComb))
}
if (evaluate) {
fit1 <- tryCatch(eval(clVariant, gmEnv), error = function(err) {
err$message <- paste(conditionMessage(err), "(model",
iComb, "skipped)", collapse = "")
class(err) <- c("simpleError", "warning", "condition")
warning(err)
return(NULL)
})
if (is.null(fit1))
next
if (nExtra != 0L) {
extraResult1 <- applyExtras(fit1)
if (length(extraResult1) < nExtra) {
tmp <- rep(NA_real_, nExtra)
tmp[match(names(extraResult1), names(extraResult))] <- extraResult1
extraResult1 <- tmp
}
}
mcoef1 <- eval(matchCoefCall)
ll1 <- logLik(fit1)
nobs1 <- nobs(fit1)
if (nobs1 != gmNobs)
cry(, "number of observations in model #%d [%d] different from that in global model [%d]",
iComb, nobs1, gmNobs, warn = TRUE)
row1 <- c(mcoef1[allTerms], extraResult1, df = attr(ll1,
"df"), ll = ll1, ic = IC(fit1))
k <- k + 1L
rvlen <- nrow(rval)
if (retNeedsExtending <- k > rvlen) {
nadd <- min(resultChunkSize, ncomb - rvlen)
rval <- rbind(rval, matrix(NA_real_, ncol = rvNcol,
nrow = nadd), deparse.level = 0L)
addi <- seq.int(rvlen + 1L, length.out = nadd)
coefTables[addi] <- vector("list", nadd)
}
rval[k, retColIdx] <- row1
coefTables[[k]] <- attr(mcoef1, "coefTable")
}
else {
k <- k + 1L
rvlen <- length(ord)
if (retNeedsExtending <- k > rvlen) {
nadd <- min(resultChunkSize, ncomb - rvlen)
addi <- seq.int(rvlen + 1L, length.out = nadd)
}
}
if (retNeedsExtending) {
calls[addi] <- vector("list", nadd)
ord[addi] <- integer(nadd)
}
ord[k] <- iComb
calls[[k]] <- clVariant
}
if (k == 0L)
stop("result is empty")
ord <- ord + 1L
names(calls) <- ord
if (!evaluate)
return(calls[seq_len(k)])
if (k < nrow(rval)) {
i <- seq_len(k)
rval <- rval[i, , drop = FALSE]
ord <- ord[i]
calls <- calls[i]
coefTables <- coefTables[i]
}
if (nVarying) {
varlev <- ord%%nVariants
varlev[varlev == 0L] <- nVariants
rval[, nVars + seq_len(nVarying)] <- variants[varlev,
]
}
rval <- as.data.frame(rval)
row.names(rval) <- ord
tfac <- which(!(allTerms %in% gmCoefNames))
rval[tfac] <- lapply(rval[tfac], factor, levels = NaN, labels = "+")
rval[, seq_along(allTerms)] <- rval[, v <- order(termsOrder)]
allTerms <- allTerms[v]
colnames(rval) <- c(allTerms, varyingNames, extraNames, "df",
lik$name, ICName)
if (nVarying) {
variant.names <- vapply(variantsFlat, asChar, "", width.cutoff = 20L)
vnum <- split(seq_len(sum(vlen)), rep(seq_len(nVarying),
vlen))
names(vnum) <- varyingNames
for (i in varyingNames) rval[, i] <- factor(rval[, i],
levels = vnum[[i]], labels = variant.names[vnum[[i]]])
}
rval <- rval[o <- order(rval[, ICName], decreasing = FALSE),
]
coefTables <- coefTables[o]
rval$delta <- rval[, ICName] - min(rval[, ICName])
rval$weight <- Weights(rval$delta)
mode(rval$df) <- "integer"
structure(rval, model.calls = calls[o], global = global.model,
global.call = gmCall, terms = structure(allTerms, interceptLabel = interceptLabel),
rank = IC, beta = strbeta, call = match.call(expand.dots = TRUE),
coefTables = coefTables, nobs = gmNobs, vCols = varyingNames,
column.types = {
colTypes <- c(terms = length(allTerms), varying = length(varyingNames),
extra = length(extraNames), df = 1L, loglik = 1L,
ic = 1L, delta = 1L, weight = 1L)
column.types <- rep(1L:length(colTypes), colTypes)
names(column.types) <- colnames(rval)
lv <- 1L:length(colTypes)
factor(column.types, levels = lv, labels = names(colTypes)[lv])
}, class = c("model.selection", "data.frame"))
}
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