Dear R experts,
I am observing undesired behavior of predict(fit, newdata), in case when fit
object is produced by lm() involving a poly(). Here is how to reproduce:
x <- c(1:10)
y <- sin(c(1:10))
fit <- lm(formula=y~poly(x, 5, raw=TRUE))
predict(fit, newdata=data.frame(x=c(1:10))) ## this works
predict(fit, newdata=data.frame(x=c(1:1))) ## this is broken, error below
Error in poly(x, 5, raw = TRUE) :
'degree' must be less than number of unique points
The problem is in poly():
if (raw) {
if (degree >= length(unique(x)))
stop("'degree' must be less than number of unique
points")
This assertion is only warranted when poly is used to fit a model. But it is
unnecessary and undesired if poly() is used to obtain prediction. Or am I
missing something?
Why I would want to obtain model prediction for a single point is another story.
I am filling a matrix of model values one element at a time, so that the matrix
can then be given to persp() (I am fitting a two-variable model).
Alex Stolpovsky
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