Nothing
iamb.glmbs <- function(target, dataset, threshold = 0.05, wei = NULL, test = NULL) {
threshold <- log(threshold)
dm <- dim(dataset)
n <- dm[1] ## sample size
p <- dm[2] ## number of variables
if ( p > n ) {
res <- paste("The number of variables is hiher than the sample size. No backward procedure was attempted")
} else {
dataset <- as.data.frame(dataset)
##################################
# target checking and initialize #
##################################
if ( !is.null(test) ) {
ci_test <- test
if ( test == "testIndBinom" ) {
wei <- target[, 2]
target <- target[, 1] / wei
funa <- internaliamb.binombs
} else if (test == "testIndLogistic" ) {
funa <- internaliamb.binombs
} else if ( test == "tesIndPois" ) {
funa <- internaliamb.poisbs
} else funa <- internaliamb.lmbs
} else {
if ( length( unique(target) ) == 2 ) {
ci_test <- "testIndLogistic"
funa <- internaliamb.binombs
} else if ( is.matrix(target) ) {
ci_test <- "testIndBinom"
} else if ( length( unique(target) ) > 2 & sum(target - round(target)) == 0 ) {
ci_test <- "testIndPois"
funa <- internaliamb.poisbs
} else {
ci_test <- "testIndReg"
funa <- internaliamb.lmbs
}
}
a1 <- funa( target = target, dataset = dataset, threshold = threshold, wei = wei, p = p )
ind <- 1:p
a2 <- list()
poies <- a1$mat[, 1]
if ( length(poies) > 0 ) {
ind[-poies] <- 0
ind <- ind[ind > 0]
dat <- dataset[, poies, drop = FALSE ]
a2 <- funa(target = target, dataset = dat, threshold = threshold, wei = wei, p = length(ind) )
poies <- a2$mat[, 1]
ind[-poies] <- 0
ind <- ind[ind > 0]
dat <- dat[, poies, drop = FALSE]
i <- 2
} else {
ind <- NULL
a2$mat <- NULL
}
while ( length(a1$mat[, 1]) - length(a2$mat[, 1]) != 0 ) {
i <- i + 1
a1 <- a2
a2 <- funa( target = target, dataset = dat, threshold = threshold, wei = wei, p = length(ind) )
poies <- a2$mat[, 1]
if ( length(poies) > 0 ) {
ind[-poies] <- 0
ind <- ind[ind > 0]
dat <- dat[, poies, drop = FALSE]
} else {
ind <- NULL
dat <- NULL
}
}
res <- list(info = ind, mat = a2$mat, ci_test = ci_test, final = a2$final )
}
res
}
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