Description Usage Arguments Value Examples
q_mv2
is the emission part of the Q function in E-step,
i.e.: Sum_i,t,k log[fk(x_t)] * L^i_k(t). (with negative sign).
q_mv2
uses mean-parametrization to calculates the target function for each k
instead of all k.
1 | q_mv2(pars, X, E, L, k)
|
pars |
a vector of length 2. c(v[k], m[k]) |
X |
a list of vectors of observed states x |
E |
a vector of normalizing constant for each observed chain in X |
L |
a list of matrix L from |
k |
a scalar indicating which state is calculated |
A scalar, the (negative) value of the target function that would later be minimized.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | df <- uORF[1:10]
X <- L <- list()
E <- c()
for (i in 1:length(df)){
X[[i]] <- df[[i]]$x
RNA[[i]] <- df[[i]]$RNA
E[i]=df[[i]]$E; trans=df[[i]]$trans;
a=df[[i]]$v; b=df[[i]]$v/df[[i]]$m
la <- forwardAlg(X[[i]], RNA[[i]], trans, a, b, E[i])
lb <- backwardAlg(X[[i]], RNA[[i]], trans, a, b, E[i])
L[[i]] <- computeL(la, lb)
}
pars <- c(df[[1]]$v, df[[1]]$m)
qe <- 0
for (k in 1:21){
qe <- qe + q_mv2(pars[c(k,21+k)],X,E,L,k)
}
print(qe)
# qemiss() uses a,b instead of v,m
pars <- c(df[[1]]$v, df[[1]]$v/df[[1]]$m)
print(qemiss(pars,X,E,L))
|
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