Please do not send HTML (as the posting guide asks) -- it has made your
code unreadable.
Also, without seeing an example we don't know if the 'completely
different' is in the output or corresponds to very different fitted
models.
There is no 'armaFit' in R: it seems you may be using package fArma or
armafit from package timsac.
What you have missed is arima() in base R, and perhaps (it is less often
useful for this model) gls() in the recommended package nlme.
I suggest you try arima(), and if that does not solve this follow the
footer of this message.
On Thu, 22 May 2008, Daphne Renault wrote:
Hi,
how to estimate a the following model in R:
y(t)=beta0+beta1*x1(t)+beta2*x2(t)+...+beta5*x5(t)+beta6*y(t-1)+beta7*y(t-2)+beta8*y(t-3)
1) using "lm" :
dates <- as.Date(data.df[,1])
selection<-which(dates>=as.Date("1986-1-1") &
dates<=as.Date("2007-12-31"))
dep <- ts(data.df[selection,c("dep")])
indep.ret1 <- ts(data.df[selection,c("RET1")])
indep.ret2 <- ts(data.df[selection,c("RET2")])
indep.ret3 <- ts(data.df[selection,c("RET3")])
indep.ret4 <- ts(data.df[selection,c("RET4")])
indep.ret5 <- ts(data.df[selection,c("RET5")])
d<-ts.union(dep,indep.ret1,indep.ret2,indep.ret3,indep.ret4,indep.ret5,dep.lag1=lag(dep,-1),dep.lag2=lag(dep,-2),dep.lag3=lag(dep,-3))
fit1 <-
lm(dep~indep.ret1+indep.ret2+indep.ret3+indep.ret4+indep.ret5+dep.lag1+dep.lag2+dep.lag3,data=d)
summary(fit1)
#coeftest(fit1,vcov=NeweyWest)
2) using armaFit:
fit2<-armaFit(dep~ar(3),xreg=ts(data.df[selection,c("RET1","RET2","RET3","RET4","RET5")]),data=ts(data.df[selection,-1]))
summary(fit2)
The results of 1) and 2) are completely different. Does anybody have an
explanation for this?
The dependent and some independent variables are autocorrelated because of
overlapping observations (but do not posess a unit root). Therefore I have
added lagged dependent variables as additional regressors to resolve the
problem of autocorrelation in the dependent variables. To account for residual
autocorrelation in the residuals I want to use the procedure of Newey West. Is
this idea absolute nonsense?
Kind regards,
Daphne
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--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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