[valse.git] / reports / essai16mars.R

p = 10
q = 8
k = 2
D = 20

meanX = matrix(nrow=p,ncol=k)
meanX[,1] = rep(0,p)
meanX[,2] = rep(1,p)

covX = array(dim=c(p,p,k))
covX[,,1] = 0.1*diag(p)
covX[,,2] = 0.5*diag(p)

covY = array(dim = c(q,q,k))
covY[,,1] = 0.1*diag(q)
covY[,,2] = 0.2*diag(q)

beta = array(dim = c(p,q,2))
beta[,,2] = matrix(c(rep(2,(D)),rep(0, p*q-D)))
beta[,,1] = matrix(c(rep(1,D),rep(0, p*q-D)))

n = 100

pi = c(0.4,0.6)

data = generateXY(meanX,covX,covY, pi, beta, n)

X = data$X
Y = data$Y

res_valse = valse(X,Y)
Commit	Line	Data
	1	p = 10
	2	q = 8
	3	k = 2
	4	D = 20
	5
	6	meanX = matrix(nrow=p,ncol=k)
	7	meanX[,1] = rep(0,p)
	8	meanX[,2] = rep(1,p)
	9
	10	covX = array(dim=c(p,p,k))
	11	covX[,,1] = 0.1*diag(p)
	12	covX[,,2] = 0.5*diag(p)
	13
	14	covY = array(dim = c(q,q,k))
	15	covY[,,1] = 0.1*diag(q)
	16	covY[,,2] = 0.2*diag(q)
	17
	18	beta = array(dim = c(p,q,2))
	19	beta[,,2] = matrix(c(rep(2,(D)),rep(0, p*q-D)))
	20	beta[,,1] = matrix(c(rep(1,D),rep(0, p*q-D)))
	21
	22	n = 100
	23
	24	pi = c(0.4,0.6)
	25
	26	data = generateXY(meanX,covX,covY, pi, beta, n)
	27
	28	X = data$X
	29	Y = data$Y
	30
	31	res_valse = valse(X,Y)