search for: wagefn

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2017 Nov 07
2
Using MLE on a somewhat unusual likelihood function
...ing 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) {...
2017 Nov 07
0
Using MLE on a somewhat unusual likelihood function
...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,])) > } e...