So I am trying to use the mle command (from stats4 package) to estimate a
number of parameters using data but it keeps throwing up this error message:
Error in solve.default(oout$hessian) :
Lapack routine dgesv: system is exactly singular: U[1,1] = 0
This error sometimes indicates that the list of starting values is too far
from optimum but this is unlikely since I picked values close to where the
parameters usually end up. I have also tried switching these around a bit.
Here is the code:
xhat = c(statemw-(1-alpha)*rval)
survivalf <- function(x) {(1-plnorm(statemw,mean=mu,sd=logalpha))}
wagefn <- function(lam, eta, alpha, xhat, mu, logalpha) {
n=nrow(cpsdata2)
wagevec = matrix(nrow=n,ncol=1)
for (i in 1:n) {
if (cpsdata2[i,2] > 0){
wagevec[i,] <-
c(eta*lam*survivalf(statemw)*exp(-lam*survivalf(statemw)*cpsdata2[i,2,]))
} else if (cpsdata2[i,1,]==statemw) {
wagevec[i,] <-
c(lam*(survivalf(statemw)-survivalf((statemw-(1-alpha)*xhat)/alpha))/(eta+lam*survivalf(statemw)))
} else if (cpsdata2[i,1,]>statemw) {
wagevec[i,] <-
c(lam*plnorm((cpsdata2[i,1,]-(1-alpha)*xhat)/alpha,mean=mu,sd=logalpha)/(alpha*(eta+lam*survivalf(statemw))))
}
else {
wagevec[i,] <- NA
}
}
lnwagevec <- log(wagevec)
-sum(lnwagevec>-200 & ln2wagevec<200, na.rm=TRUE)
}
fit <- mle(wagefn, start=listmat, method= "L-BFGS-B",lower=
c(-Inf,0),upper=c(Inf,Inf)
I know the likelihood function is a handful but it does return a reasonable
looking vector of values. The "lnwagevec>-200" etc is an inelegant way of
preventing values of Inf and -Inf from entering the sum, the actual values
rarely go as high as 8 or low as -5.
Thank you in advance to anyone responding!
/Hugo
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