G'day John,
For these snippets to produce what I think you want them to produce it
is just necessary to define doit() as follows:
doit <- function(x){
lm(formula=x)
}
R> # run formula y~x
R> JD <- doit(y~x)
R> JD
Call:
lm(formula = x)
Coefficients:
(Intercept) x
0.8403 0.8558
R> # run formula y~x+z
R> JD2 <- doit(y~x+z)
R> JD2
Call:
lm(formula = x)
Coefficients:
(Intercept) x z
-0.7490 0.6237 1.9023
Cheers,
Berwin
On Thu, 16 Mar 2023 14:53:33 +0000
"Sorkin, John" <jsor...@som.umaryland.edu> wrote:
> Although I owe thanks to Ramus and Ivan, I still do not know how to
> write and "advanced" function.
>
> My most recent try (after looking at the material Ramus and Ivan set)
> still does not work. I am trying to run the lm function on two
> different formulae: 1) y~x, 2) y~x+z
> Any corrections would be appreciated!
>
> Thank you,
> John
>
>
> doit <- function(x){
> ds <- deparse(substitute(x))
> cat("1\n")
> print(ds)
> eval(lm(quote(ds)),parent.frame())
> }
>
> # define data that will be used in regression
> y <- 1:10
> x <- y+rnorm(10)
> z <- c(rep(1,5),rep(2,5))
> # Show what x, y and z look like
> rbind(x,y,z)
>
> # run formula y~x
> JD <- doit(y~x)
> JD
>
> # run formula y~x+z
> JD2 <- doit(y~x+z)
> JD2
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