-## ace.R (2009-01-19)
+## ace.R (2009-03-22)
## Ancestral Character Estimation
if (output.liks) return(liks[-(1:nb.tip), ])
- 2 * log(sum(liks[nb.tip + 1, ]))
}
- out <- nlm(function(p) dev(p), p = rep(ip, length.out = np),
- hessian = TRUE)
- obj$loglik <- -out$minimum / 2
- obj$rates <- out$estimate
- if (any(out$gradient == 0))
+ out <- nlminb(rep(ip, length.out = np), function(p) dev(p),
+ lower = rep(0, np), upper = rep(Inf, np))
+ obj$loglik <- -out$objective/2
+ obj$rates <- out$par
+ oldwarn <- options("warn")
+ options(warn = -1)
+ h <- nlm(function(p) dev(p), p = obj$rates, iterlim = 1,
+ stepmax = 0, hessian = TRUE)$hessian
+ options(oldwarn)
+ if (any(h == 0))
warning("The likelihood gradient seems flat in at least one dimension (gradient null):\ncannot compute the standard-errors of the transition rates.\n")
- else obj$se <- sqrt(diag(solve(out$hessian)))
+ else obj$se <- sqrt(diag(solve(h)))
obj$index.matrix <- index.matrix
if (CI) {
lik.anc <- dev(obj$rates, TRUE)