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.
