linpred {Eplot}  R Documentation 
Provides linear regression based predictions from a y~x
type model
using recursive or rolling regression.
linpred(y, x, h = 1, wind = NULL, rr = c("Rec"))
y 
a series to be predicted 
x 
a numeric or matrix of explanatory variables 
h 
The horizon for which you would like to have the prediction for (see details) 
wind 
the size of the rolling window or the initial training period if recursive is used 
rr 
recursive or rolling window? Possible values are

The training is done using the direct method: y_{1 : (t+h1)} = \beta
x_{1:(t1)} + \varepsilon_{1:(t+h1)}
and the forecast is made at time
(t+h) as \widehat{y}_{t+h} = \widehat{\beta} x_t
.
vector of prediction values with the same dimension as the original
series. The first wind
values are NA's
x = rnorm(100)
lx < lagmat(x,2)
tail(lx)
tail(x)
out < linpred(x,lx)
plott(x, return.to.default=FALSE)
plott(out,add=TRUE,col=2)