Commit 23f5e65a authored by GD's avatar GD

mean of noise on latent variable is set to 0

parent 5b658252
......@@ -13,10 +13,10 @@ beta.min = 5
beta.max = 10
mean.H=0
sigma.H=10
mean.F=0
sigma.F=5
sample1 = sample.bin(n, p, kstar, lstar, beta.min, beta.max, mean.H, sigma.H, mean.F, sigma.F)
sample1 = sample.bin(n, p, kstar, lstar, beta.min, beta.max,
mean.H, sigma.H, sigma.F, seed = NULL)
X = sample1$X
Y = sample1$Y
......
......@@ -97,8 +97,6 @@
#' \item{mean.H}{the mean of latent variables used to generates \code{X}.}
#' \item{sigma.H}{the standard deviation of latent variables used to
#' generates \code{X}.}
#' \item{sigma.F}{the mean of the noise added to latent
#' variables used to generates \code{X}.}
#' \item{sigma.F}{the standard deviation of the noise added to latent
#' variables used to generates \code{X}.}
#' \item{seed}{an positive integer, if non NULL it fix the seed
......@@ -125,13 +123,13 @@
#' p <- 1000
#' sample1 <- sample.bin(n=n, p=p, kstar=20, lstar=2, beta.min=0.25,
#' beta.max=0.75, mean.H=0.2,
#' sigma.H=10, mean.F=0, sigma.F=5)
#' sigma.H=10, sigma.F=5)
#'
#' str(sample1)
#'
#' @export
sample.bin = function(n, p, kstar, lstar, beta.min, beta.max,
mean.H=0, sigma.H=1, mean.F=0, sigma.F=1, seed=NULL) {
mean.H=0, sigma.H=1, sigma.F=1, seed=NULL) {
### input
# n : sample size
......
......@@ -133,7 +133,8 @@
#' str(sample1)
#'
#' @export
sample.multinom = function(n, p, nb.class=2, kstar, lstar, beta.min, beta.max, mean.H=0, sigma.H, sigma.F, seed=NULL) {
sample.multinom = function(n, p, nb.class=2, kstar, lstar, beta.min, beta.max,
mean.H=0, sigma.H=1, sigma.F=1, seed=NULL) {
### input
# n : sample size
......
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