Perhaps I'm just being obtuse, but I don't see what ols() has to do with
the question that was asked.
Often with R it is easier to roll your own rather than struggling
with the
arcana of someone else's software.
Here is a function that seems to do what Ben wants:
pecb <- function(fit,tt,alp
On Mon, Jun 15, 2009 at 6:57 PM, Ben Amsel wrote:
> Hello R users,
>
> Given a linear (in the parameters) regression model where one predictor x
> interacts with time and time*time (ie, a quadratic effect of time t):
> y = b0 + b1(x) + b2(t) + b3(t^2) + b4(x*t) + b5(x*t^2) + e,
>
> I would like to
Hello R users,
Given a linear (in the parameters) regression model where one predictor x
interacts with time and time*time (ie, a quadratic effect of time t):
y = b0 + b1(x) + b2(t) + b3(t^2) + b4(x*t) + b5(x*t^2) + e,
I would like to construct 95% confidence bands (optimally, shaded) around
thi
3 matches
Mail list logo
