1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
|
# last modified 2019-11-15 by J. Fox
optimizerOptim <- function(start, objective=objectiveML,
gradient=TRUE, maxiter, debug, par.size, model.description, warn, method="CG", ...){
with(model.description, {
obj <- objective(gradient=gradient)
grad <- if (gradient) obj$gradient else NULL
obj <- obj$objective
typsize <- if (par.size == 'startvalues') abs(start) else rep(1, t)
if (!warn) save.warn <- options(warn=-1)
res <- optim(start, obj, gr=grad, hessian=TRUE, control=list(maxit=maxiter, trace=if(debug) 6 else 0,
parscale=typsize), method=method, ..., model.description)
if (!warn) options(save.warn)
result <- list()
result$convergence <- res$convergence == 0
result$iterations <- if (res$convergence == 1) maxiter else NA
par <- res$par
names(par) <- param.names
result$par <- par
if (!result$convergence)
warning(paste('Optimization may not have converged; optim return code = ',
res$convergence, '. Consult ?optim.\n', sep=""))
vcov <- matrix(NA, t, t)
qr.hess <- try(qr(res$hessian), silent=TRUE)
if (inherits(qr.hess, "try-error")){
warning("Could not compute QR decomposition of Hessian.\nOptimization probably did not converge.\n")
}
else if (qr.hess$rank < t){
warning(' singular Hessian: model is probably underidentified.\n')
which.aliased <- qr.hess$pivot[-(1:qr.hess$rank)]
result$aliased <- param.names[which.aliased]
}
else {
vcov <- (2/(N - (!raw))) * solve(res$hessian)
if (any(diag(vcov) < 0)) {
result$aliased <- param.names[diag(vcov) < 0]
warning("Negative parameter variances.\nModel may be underidentified.\n")
}
}
colnames(vcov) <- rownames(vcov) <- param.names
result$vcov <- vcov
result$criterion <- res$value
if (!raw) {
CC <- diag(diag(S))
result$chisqNull <- (N - 1) *
(sum(diag(S %*% solve(CC))) + log(det(CC)) - log(det(S)) - n)
}
obj <- obj(par, model.description)
C <- attr(obj, "C")
rownames(C) <- colnames(C) <- var.names[observed]
result$C <- C
A <- attr(obj, "A")
rownames(A) <- colnames(A) <- var.names
result$A <- A
P <- attr(obj, "P")
rownames(P) <- colnames(P) <- var.names
result$P <- P
class(result) <- "semResult"
result
}
)
}
|
