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I am assuming the variable out is the output parameter. However, I don't understand what is out[1+xi*xx>0]? Can someone explain this to me? Thanks in advance, Chen dGEV <- function(x, xi, mu = 0, sigma = 1, logvalue=FALSE) { xx <- (x-mu)/sigma #use the new dGumbel which passes mu and sigma: #if (xi==0) out <- dGumbel(xx,logvalue=TRUE)-log(sigma) if (xi==0) { return(out <- dGumbel(x, mu, sigma, logvalue)); } else { out <- rep(-Inf,length(x)) out[1+xi*x...

...(t, theta) { lambda <- theta[1] chi <- theta[2] psi <- theta[3] if (chi==0) out <- (1+2*t/psi)^(-lambda) else if (psi==0) out <- 2^(lambda+1)*exp(besselM3(lambda,sqrt(2*chi*t),log value=TRUE)-lambda*log(2*chi*t)/2)/gamma(-lambda) else out <- exp(besselM3(lambda,sqrt(chi*(psi+2*t)),logvalue=T RUE)+lambda*log(chi*psi)/2-besselM3(lambda,sqrt(chi*psi),logvalue=TRUE)-lambda*log(chi*(psi+2*t))/2) out } ) phi.inverse( - log(U)/Y, theta) } -- View this message in context: http://www.nabble.com/Newbie-that-don%27t-understand-R-code-tp25009034p25009034.html Sent from the R help mailing list a...

...-mu gammathelda<-thelda*gamma sigmathelda<-(thelda^2)*sigma betathelda<-(thelda^2)*sigma*beta lambdastar<-lambda-0.5 theldastar[i]<-sqrt(1+((y[i]-muthelda)/sigmathelda)^2) gammastar<-sqrt((gammathelda^2)+((betathelda/sigmathelda)^2)) klambda1<-besselM3(lambdastar+1, x=2, logvalue=FALSE) klambda<-besselM3(lambdastar,x=2,logvalue=FALSE) klambda2<-besselM3(lambdastar-1,x=2,logvalue=FALSE) zi[i]<-((theldastar[i]*klambda1*(theldastar[i]*gammastar))/(gammastar*klambda*theldastar[i]*gammastar)) ti[i]<-((gammastar*klambda2*(theldastar[i]*gammastar))/(theldastar[i]*k...

...ma))/pi) mu0 <- mean(maxima) - 0.57722 * sigma0 xi0 <- 0.1 theta <- c(xi0, mu0, sigma0) #10/5/2007: removed assign() for maxima.nl #10/5/2007: passed additional parameter to avoid using assign() negloglik <- function(theta, maxvalue) { -sum(dGEV(maxvalue,theta[1],theta[2],abs(theta[3]),logvalue=TRUE)); } #10/5/2007: passed additional 4th parameter which will be passed to negloglik optimfit <- optim(theta, fn=negloglik, gr=NULL, maxvalue=maxima, method="BFGS"); par.ests <- optimfit$par; if(optimfit$convergence == 0) #if code is 0 we are OK; converged <- TRUE else conv...