Commit | Line | Data |
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d1531659 | 1 | #----------------------------------------------------------------------- |
2 | #' Initialize the parameters in a basic way (zero for the conditional mean, | |
e166ed4e | 3 | #' uniform for weights, identity for covariance matrices, and uniformly distributed forthe clustering) |
d1531659 | 4 | #' @param n sample size |
5 | #' @param p number of covariates | |
6 | #' @param m size of the response | |
7 | #' @param k number of clusters | |
8 | #' @return list with phiInit, rhoInit,piInit,gamInit | |
9 | #' @export | |
10 | #----------------------------------------------------------------------- | |
39046da6 BA |
11 | basic_Init_Parameters = function(n,p,m,k) |
12 | { | |
e166ed4e BA |
13 | phiInit = array(0, dim=c(p,m,k)) |
14 | ||
15 | piInit = (1./k)*rep.int(1,k) | |
16 | ||
17 | rhoInit = array(0, dim=c(m,m,k)) | |
18 | for(i in 1:k) | |
19 | rhoInit[,,i] = diag(m) | |
20 | ||
21 | gamInit = 0.1*array(1, dim=c(n,k)) | |
22 | R = sample(1:k,n, replace=TRUE) | |
23 | for(i in 1:n) | |
24 | gamInit[i,R[i]] = 0.9 | |
25 | gamInit = gamInit/sum(gamInit[1,]) | |
26 | ||
27 | return (data = list(phiInit = phiInit, rhoInit = rhoInit, piInit = piInit, gamInit = gamInit)) | |
35b42a4b | 28 | } |