check_identifiable() crashes when eigenvalues of "covariance" matrix are complex

[wStockhausen]

check_identifiable() crashes when eigenvalues of a bad "covariance" matrix are complex. The following code handles the situation without blowing up. Might want to add an error message pointing out why the check failed.

check_identifiable <- function(model, path=getwd()){

Check eigendecomposition

fit <- adnuts:::.read_mle_fit(model, path)
hes <- adnuts:::.getADMBHessian(path)
ev <- eigen(hes);
if (any(is.complex(ev$values))){
WhichBad <- which( abs(Im(ev$values)) > .Machine$double.eps);
} else {
WhichBad <- which( ev$values < sqrt(.Machine$double.eps) );
}

if(length(WhichBad)==0){
message( "All parameters are identifiable" )
} else {
## Check for parameters
if(length(WhichBad)==1){
RowMax <- abs(ev$vectors[,WhichBad])
} else {
RowMax <- apply(ev$vectors[, WhichBad], MARGIN=1, FUN=function(vec){max(Mod(vec))} )
}
bad <- data.frame(ParNum=1:nrow(hes), Param=fit$par.names,
MLE=fit$est[1:nrow(hes)],
Param_check=ifelse(RowMax>0.1, "Bad","OK"))
row.names(bad) <- NULL
bad <- bad[bad$Param_check=='Bad',]
print(bad)
return(invisible(bad))
}
}

[Cole-Monnahan-NOAA]

@wStockhausen sorry for the delay I was not alerted to this issue for some reason.

I implemented your fix in this commit. If you have time could you confirm it works? I haven't run across a matrix with complex eigenvalues yet.