[prev in list] [next in list] [prev in thread] [next in thread] 

List:       r-help
Subject:    [R] gls with serial correlation
From:       Wayne Jones <JonesW () kssg ! com>
Date:       2003-11-21 12:55:51
[Download RAW message or body]


Hello there fellow R users, 

Im trying to fit a gls model to data which has serial correlation in the
errors e(t)=p*e(t-1). 
However I dont seem to be having much luck in erradicating the
autocorrelation in the residuals. 

I have created the following example.

library(nlme)
x<-rnorm(100)
y<-3+2*x
y<-y+arima.sim(100,model=list(ar=(0.6)))+rnorm(100,0,0.2)
#Create a data set with first order serial correlation in the residuals.



my.mat<-as.data.frame(cbind(y,x))
acf(lm(y~x,my.mat)$residuals)  #fit a linear model and observe the
residuals.


acf(as.numeric(gls(y~x,my.mat,correlation = corAR1())$residuals));  # fit a
gls model with correlated error terms and observe autocorrelation of
residuals


Further more if I use time series fitting I get a different result. 


library(ts)
acf(arima(as.ts(y),xreg=x,order=c(1,0,0))$residuals) # fit a time series
model and observe the residuals


I must be doing something wrong. 

Am I using the correct correlation structure (corAr1).


Thanks in advance,

Wayne


Dr Wayne R. Jones
Senior Statistician / Research Analyst
KSS Limited
St James's Buildings
79 Oxford Street
Manchester M1 6SS
Tel: +44(0)161 609 4084
Mob: +44(0)7810 523 713




KSS Ltd
Seventh Floor  St James's Buildings  79 Oxford Street  Manchester  M1 6SS  England
Company Registration Number 2800886
Tel: +44 (0) 161 228 0040	Fax: +44 (0) 161 236 6305
mailto:kssg@kssg.com		http://www.kssg.com


The information in this Internet email is confidential and m...{{dropped}}


[prev in list] [next in list] [prev in thread] [next in thread]