http://r.789695.n4.nabble.com/file/n4619404/pic1.jpg cesres_ext <- nls(lnGDP85~ intercept + (alpha/(1-alpha-beta)) * lns_ikonngdelta + (beta/(1-alpha-beta)) * lns_ihonngdelta + 0.5 * ((sigma-1)/sigma) * (1/((1-alpha-beta)*(1-alpha-beta))) * (alpha * taylor1 + beta * taylor2 - alpha*beta*taylor3) ,start = list(intercept=8, alpha=0.2, beta=0.4, sigma=1.2),data=data) I have this model. I use the command above in R, and it gives me a desirable result. It gives me implied alpha, implied beta, and implied xicma just fine. However next I have to run another model, which is pretty much similar, however now it has theta in there. In my paper that I replicate, they only report implied alpha, implied beta, and implied xicma just like the above model, there's no theta report. So I wonder how would I put theta in this function. What role theta plays in this model. What could be the command. It seems like there's no estimation of theta. Is that theta given. In the paper they say : theta = 1 - exp(-Lt)) where L is like a convergence rate. The model looks like this: http://r.789695.n4.nabble.com/file/n4619404/pic2.jpg -- View this message in context: http://r.789695.n4.nabble.com/How-to-run-this-model-using-nonlinear-least-square-in-R-tp4619404.html Sent from the R help mailing list archive at Nabble.com.