[valse.git] / R / generateIOdefault.R

#' Generate a sample of (X,Y) of size n with default values
#' @param n sample size
#' @param p number of covariates
#' @param m size of the response
#' @param k number of clusters
#' @return list with X and Y
#' @export
#-----------------------------------------------------------------------
generateIOdefault = function(n, p, m, k)
{
  covX = array(0, dim=c(p,p,k))
  covY = array(0, dim=c(m,m,k))
  for(r in 1:k)
  {
    covX[,,r] = diag(p)
    covY[,,r] = diag(m)
  }
  
  pi = rep(1./k,k)
  
  beta = array(0, dim=c(p,m,k))
  for(j in 1:p)
  {
    nonZeroCount = ceiling(m * runif(1))
    beta[j,1:nonZeroCount,] = matrix(runif(nonZeroCount*k), ncol=k)
  }
  
  sample_IO = generateIO(covX, covY, pi, beta, n)
  return (list(X=sample_IO$X,Y=sample_IO$Y))
}
Commit	Line	Data
d1531659	1	#' Generate a sample of (X,Y) of size n with default values
	2	#' @param n sample size
	3	#' @param p number of covariates
	4	#' @param m size of the response
	5	#' @param k number of clusters
	6	#' @return list with X and Y
	7	#' @export
	8	#-----------------------------------------------------------------------
39046da6 BA	9	generateIOdefault = function(n, p, m, k)
39046da6 BA	10	{
d1531659	11	covX = array(0, dim=c(p,p,k))
	12	covY = array(0, dim=c(m,m,k))
	13	for(r in 1:k)
	14	{
	15	covX[,,r] = diag(p)
	16	covY[,,r] = diag(m)
	17	}
	18
	19	pi = rep(1./k,k)
	20
	21	beta = array(0, dim=c(p,m,k))
	22	for(j in 1:p)
	23	{
	24	nonZeroCount = ceiling(m * runif(1))
	25	beta[j,1:nonZeroCount,] = matrix(runif(nonZeroCount*k), ncol=k)
	26	}
	27
	28	sample_IO = generateIO(covX, covY, pi, beta, n)
	29	return (list(X=sample_IO$X,Y=sample_IO$Y))
39046da6	30	}