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#' @rdname plsRmulti
#' @method plsRmultiModel formula
#' @export
plsRmultiModel.formula <- function(object, data, nt = 2, limQ2set = .0975,
modele = "pls", family = NULL,
typeVC = "none", EstimXNA = FALSE,
scaleX = TRUE, scaleY = NULL,
pvals.expli = FALSE,
alpha.pvals.expli = .05,
MClassed = FALSE, tol_Xi = 10^(-12),
weights = NULL, subset = NULL, contrasts = NULL,
sparse = FALSE, sparseStop = FALSE,
naive = FALSE, verbose = TRUE, ...) {
dots <- list(...)
pls_multi_check_dots(dots)
pls_multi_reject_unsupported(
modele = modele,
family = family,
typeVC = typeVC,
weights_supplied = !missing(weights) && !is.null(weights),
limQ2set = limQ2set,
dataPredictY_supplied = FALSE,
EstimXNA = EstimXNA,
pvals.expli = pvals.expli,
alpha.pvals.expli = alpha.pvals.expli,
MClassed = MClassed,
sparse = sparse,
sparseStop = sparseStop,
naive = naive
)
if (is.null(scaleY)) {
scaleY <- TRUE
}
if (missing(data)) {
data <- environment(object)
}
built <- pls_multi_build_matrix_from_formula(
formula = object,
data = data,
subset = subset,
weights = if (missing(weights)) NULL else weights,
contrasts = contrasts
)
estmodel <- pls_multi_fit_core(
dataY = built$dataY,
dataX = built$dataX,
nt = nt,
scaleX = scaleX,
scaleY = scaleY,
tol_Xi = tol_Xi,
verbose = verbose
)
callf0 <- match.call(expand.dots = FALSE)
callf0$... <- NULL
callf0$dataY <- callf0$object
call0 <- c(toString(callf0[[1]]), names(callf0))
call1 <- call0[!(call0 == "") & !(call0 == "object")]
estmodel$call <- callf0[call1]
estmodel$call[[1L]] <- as.name(toString(callf0[[1]]))
estmodel$call$formula <- object
estmodel$scaleX <- scaleX
estmodel$scaleY <- scaleY
estmodel$terms_x <- built$terms_x
estmodel$contrasts <- built$contrasts
estmodel$xlevels <- built$xlevels
class(estmodel) <- "plsRmultiModel"
estmodel
}
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