list(
# p: dimension K-1, need to be completed
"p" = c(v[1:(K-1)], 1-sum(v[1:(K-1)])),
- "β" = matrix(v[K:(K+d*K-1)], ncol=K),
+ "β" = t(matrix(v[K:(K+d*K-1)], ncol=d)),
"b" = v[(K+d*K):(K+(d+1)*K-1)])
},
{
"Linearize vectors+matrices from list L into a vector"
- c(L$p[1:(K-1)], as.double(L$β), L$b)
+ # β linearized row by row, to match derivatives order
+ c(L$p[1:(K-1)], as.double(t(L$β)), L$b)
},
computeW = function(θ)
{
- #return (diag(c(rep(6,d), rep(3, d^2), rep(1,d^3))))
require(MASS)
dd <- d + d^2 + d^3
M <- Moments(θ)
Omega <- matrix( .C("Compute_Omega",
- X=as.double(X), Y=as.double(Y), M=as.double(M),
+ X=as.double(X), Y=as.integer(Y), M=as.double(M),
pn=as.integer(n), pd=as.integer(d),
W=as.double(W), PACKAGE="morpheus")$W, nrow=dd, ncol=dd )
MASS::ginv(Omega)
else if (!is.numeric(θ0$b) || length(θ0$b) != K || any(is.na(θ0$b)))
stop("θ0$b: length K, no NA")
# TODO: stopping condition? N iterations? Delta <= epsilon ?
- for (loop in 1:10)
+ for (loop in 1:2)
{
op_res = constrOptim( linArgs(θ0), .self$f, .self$grad_f,
ui=cbind(