I'm working with the function.
lm (y ~ x)
Simple regression, due to tests I checked autocorrelation, so the blibliography indicates a transformation. Something like:
Y = B1 * (1-p) + B2 (X- (p * X [-1]))
What would be the application of the correction P in the model, where P is known by me. Does anyone know an autocorrelation correction technique, next to the given function?
Thank you
If this is a time series, it's best to work with link , but if you really want to do this, then:
create a column of delays (lag) and p value
lag < -x
lag < -c (NA, test)
P < -rep.int (p, length (test))
example:
> te<-1:10
> te
[1] 1 2 3 4 5 6 7 8 9 10
> te<-c(NA,te)
> te
[1] NA 1 2 3 4 5 6 7 8 9 10
>p<-rep.int(0.3, length(te))
And do lm to estimate B1 and B2:
lm(y~(1-P)+(X-(P*te))
Just be careful, as all columns should be the same size.