Hi guys,
I am afraid I am stuck with an estimation problem.
I have two variables, X and Y. Y is explained by the weighted sum of n
lagged values of X. My aim is to estimate the two parameters
c(alpha0,alpha1) in:
Yt = Sum from j=1 to n of ( ( alpha0 + alpha1 * j ) * Xt-j )
Where Xt-j denotes the jth lag of X.
I came up with this approach because I thought it would be a good idea to
estimate the slope of the weights rather than estimating one parameter for
each lag of X added (I intent to set n very large). Is that easily doable
in R?
My first try looks like this:
parameters<-function(alpha,y){
logl<- for(i in 1:n){
sum((alpha[1]+alpha[2]*i)*lag(xvar,i))
}
return(-logl)
}
optim(c(0.001,0.001),parameters,y=yvar)
It is really hard to find any clear sources when it comes to optimization
including lags.
I would really appreciate if someone could help me out on this one!
Kind regards & Happy Easter,
Christian
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