Hi there, I ran the following code:
vols=read.csv(file="C:/Documents and Settings/Hugh/My Documents/PhD/Swaption vols.csv" , header=TRUE, sep=",") X<-ts(vols[,2]) #X dcOU<-function(x,t,x0,theta,log=FALSE){ Ex<-theta[1]/theta[2]+(x0-theta[1]/theta[2])*exp(-theta[2]*t) Vx<-theta[3]^2*(1-exp(-2*theta[2]*t))/(2*theta[2]) dnorm(x,mean=Ex,sd=sqrt(Vx),log=log) } OU.lik<-function(theta1,theta2,theta3){ n<-length(X) dt<-deltat(X) -sum(dcOU(X[2:n],dt,X[1:(n-1)],c(theta1,theta2,theta3),log=TRUE)) } require(stats4) require(sde) set.seed(1) #X<-sde.sim(model="OU",theta=c(3,1,2),N=10000,delta=1) mle(OU.lik,start=list(theta1=1,theta2=1,theta3=1), method="L-BFGS-B",lower=c(-Inf,-Inf,-Inf),upper=c(Inf,Inf,Inf))->fit summary(fit) #ex3.01 R prof<-profile(fit) par(mfrow=c(1,3)) plot(prof) par(mfrow=c(1,1)) vcov(fit) I run the code above and I get: > summary(fit) Maximum likelihood estimation Call: mle(minuslogl = OU.lik, start = list(theta1 = 1, theta2 = 1, theta3 = 1), method = "L-BFGS-B", lower = c(-Inf, -Inf, -Inf), upper = c(Inf, Inf, Inf)) Coefficients: Estimate Std. Error theta1 0.03595581 0.013929892 theta2 4.30910365 1.663781710 theta3 0.02120220 0.004067477 -2 log L: -5136.327 I need to run the same analysis for 40 different time series. I want to be able to collate all the estimates of theta and the associated stadard errors and then transfer them into excel? Can someone please point me to some R code that will allow me to do this? Thanks -- View this message in context: http://r.789695.n4.nabble.com/Reading-Data-from-mle-into-excel-tp3545569p3545569.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.