Question

Is there a utility to run regressions using xts objects of the following type:

lm(y ~ lab(x, 1) + lag(x, 2) + lag(x,3), data=as.data.frame(coredata(my_xts)))

where my_xts is an xts object that contains an x and a y. The point of the question is is there a way to avoid doing a bunch of lags and merges to have a data.frame with all the lags? I think that the package dyn works for zoo objects so i would expect it to work the same way with xts but though there might be something updated.

Answer 1

The dyn and dynlm packages can do that with zoo objects. In the case of dyn just write dyn$lm instead of lm and pass it a zoo object instead of a data frame.

Note that lag in xts works the opposite of the usual R convention so if x is of xts class then lag(x, 1) is the same as lag(x, -1) if x were of zoo or ts class.

> library(xts)
> library(dyn)
> x <- xts(anscombe[c("y1", "x1")], as.Date(1:11)) # test data
> dyn$lm(y1 ~ lag(x1, -(1:3)), as.zoo(x))

Call:
lm(formula = dyn(y1 ~ lag(x1, -(1:3))), data = as.zoo(x))

Coefficients:
     (Intercept)  lag(x1, -(1:3))1  lag(x1, -(1:3))2  lag(x1, -(1:3))3  
         3.80530           0.04995          -0.12042           0.46631