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Rename main function into runValse, remove testthat folder since nobody's gonna write...
[valse.git]
/
pkg
/
R
/
initSmallEM.R
diff --git
a/pkg/R/initSmallEM.R
b/pkg/R/initSmallEM.R
index
056d7e7
..
fccd51d
100644
(file)
--- a/
pkg/R/initSmallEM.R
+++ b/
pkg/R/initSmallEM.R
@@
-1,18
+1,19
@@
-#' initialization of the EM algorithm
+#' initialization of the EM algorithm
#'
#' @param k number of components
#' @param X matrix of covariates (of size n*p)
#' @param Y matrix of responses (of size n*m)
#'
#' @return a list with phiInit, rhoInit, piInit, gamInit
#'
#' @param k number of components
#' @param X matrix of covariates (of size n*p)
#' @param Y matrix of responses (of size n*m)
#'
#' @return a list with phiInit, rhoInit, piInit, gamInit
-#'
@export
+#'
#' @importFrom methods new
#' @importFrom stats cutree dist hclust runif
#' @importFrom methods new
#' @importFrom stats cutree dist hclust runif
+#' @export
initSmallEM <- function(k, X, Y, fast)
{
initSmallEM <- function(k, X, Y, fast)
{
- n <- nrow(Y)
- m <- ncol(Y)
+ n <- nrow(X)
p <- ncol(X)
p <- ncol(X)
+ m <- ncol(Y)
nIte <- 20
Zinit1 <- array(0, dim = c(n, nIte))
betaInit1 <- array(0, dim = c(p, m, k, nIte))
nIte <- 20
Zinit1 <- array(0, dim = c(n, nIte))
betaInit1 <- array(0, dim = c(p, m, k, nIte))
@@
-34,12
+35,12
@@
initSmallEM <- function(k, X, Y, fast)
for (r in 1:k)
{
Z <- Zinit1[, repet]
for (r in 1:k)
{
Z <- Zinit1[, repet]
- Z_indice <- seq_len(n)[Z == r] #renvoit les indices o
รน
Z==r
+ Z_indice <- seq_len(n)[Z == r] #renvoit les indices o
u
Z==r
if (length(Z_indice) == 1) {
if (length(Z_indice) == 1) {
- betaInit1[, , r, repet] <- MASS::ginv(crossprod(t(X[Z_indice, ]))) %*%
+ betaInit1[, , r, repet] <- MASS::ginv(crossprod(t(X[Z_indice, ]))) %*%
crossprod(t(X[Z_indice, ]), Y[Z_indice, ])
} else {
crossprod(t(X[Z_indice, ]), Y[Z_indice, ])
} else {
- betaInit1[, , r, repet] <- MASS::ginv(crossprod(X[Z_indice, ])) %*%
+ betaInit1[, , r, repet] <- MASS::ginv(crossprod(X[Z_indice, ])) %*%
crossprod(X[Z_indice, ], Y[Z_indice, ])
}
sigmaInit1[, , r, repet] <- diag(m)
crossprod(X[Z_indice, ], Y[Z_indice, ])
}
sigmaInit1[, , r, repet] <- diag(m)
@@
-54,10
+55,11
@@
initSmallEM <- function(k, X, Y, fast)
{
dotProduct <- tcrossprod(Y[i, ] %*% rhoInit1[, , r, repet]
- X[i, ] %*% phiInit1[, , r, repet])
{
dotProduct <- tcrossprod(Y[i, ] %*% rhoInit1[, , r, repet]
- X[i, ] %*% phiInit1[, , r, repet])
- Gam[i, r] <- piInit1[repet, r] *
+ Gam[i, r] <- piInit1[repet, r] *
det(rhoInit1[, , r, repet]) * exp(-0.5 * dotProduct)
}
sumGamI <- sum(Gam[i, ])
det(rhoInit1[, , r, repet]) * exp(-0.5 * dotProduct)
}
sumGamI <- sum(Gam[i, ])
+ # TODO: next line is a division by zero if dotProduct is big
gamInit1[i, , repet] <- Gam[i, ]/sumGamI
}
gamInit1[i, , repet] <- Gam[i, ]/sumGamI
}