Great, thanks again, Duncan. And to Peter. I've adopted the enclos =
environment(formula)
solution.
Roger
On Apr 12, 2009, at 2:29 PM, Duncan Murdoch wrote:
roger koenker wrote:
Thanks. Yes, I wrote rqss, and attempted to follow the structure
of lm, and various analogues,
for example
roger koenker wrote:
Thanks. Yes, I wrote rqss, and attempted to follow the structure of
lm, and various analogues,
for example in survival4. My problem seems to be that my lam variable
is not part of
the data frame d, and I don't know how to manipulate the environment for
the formula
so t
roger koenker wrote:
Thanks. Yes, I wrote rqss, and attempted to follow the structure of
lm, and various analogues,
for example in survival4. My problem seems to be that my lam variable
is not part of
the data frame d, and I don't know how to manipulate the environment
for the formula
s
Thanks. Yes, I wrote rqss, and attempted to follow the structure of
lm, and various analogues,
for example in survival4. My problem seems to be that my lam variable
is not part of
the data frame d, and I don't know how to manipulate the environment
for the formula
so that it is found. T
On 11/04/2009 6:50 PM, roger koenker wrote:
I'm having difficulty with an environmental issue: I have an additive
model fitting function
with a typical call that looks like this:
require(quantreg)
n <- 100
x <- runif(n,0,10)
y <- sin(x) + rnorm(n)/5
d <- data.frame(x,y)
lam <- 2
f <-
I'm having difficulty with an environmental issue: I have an additive
model fitting function
with a typical call that looks like this:
require(quantreg)
n <- 100
x <- runif(n,0,10)
y <- sin(x) + rnorm(n)/5
d <- data.frame(x,y)
lam <- 2
f <- rqss(y ~ qss(x, lambda = lam), data = d)
th
