Commit 23f5e65a by 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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