After rereading Rui Barrades's reply, I was able to get "lm" object from
data.table
carsreg3 <- carsdt[, .(fit = list(lm(mpg ~ disp + hp + wt))), by = .(cyl)]
carsreg3[, .N]
#[1] 3
carsreg3[(cyl == 6), .(fit)][[1]][[1]] |> class()
#[1] "lm"
carsreg3[(cyl == 6), .(fit)][[1]][[1]] |> summary()
car
В Sun, 22 Sep 2024 07:44:16 -0400
Naresh Gurbuxani пишет:
> carsreg <- carsdt[, .(fit = lm(mpg ~ disp + hp + wt)), by = .(cyl)]
>
> #I would like a data.table with three rows, one each for "lm" object
> corresponding to cyl value
>
> carsreg[, .N]
> #[1] 36
Try wrapping the lm() expression in
Thanks everyone for their responses.
My data is organized in a data.table. My goal is to perform analyses
according to some groups. The results of analysis are objects. If
these objects could be stored as elements of a data.table, this would
help downstream summarizing of results.
Let me
Well, you may have good reasons to do things this way -- and you
certainly do not have to explain them here.
But you might wish to consider using R's poly() function and a basic
nested list structure to do something quite similar that seems much
simpler to me, anyway:
x <- rnorm(20)
df <- data.fr
I think there is a typo in your reprex l(x^2) ??
mydt[1,2] contains a list. Which when unlisted contains a load of data.
I'm not sure what you are asking for? Are you trying to unlist that and
have it as a row? Sort of pivot.wider if you like or unnest in tidyverse
concepts?
I think the data.tab
Às 22:25 de 21/09/2024, Naresh Gurbuxani escreveu:
I am trying to store regression objects in a data.table
df <- data.frame(x = rnorm(20))
df[, "y"] <- with(df, x + 0.1 * x^2 + 0.2 * rnorm(20))
mydt <- data.table(mypower = c(1, 2), myreg = list(lm(y ~ x, data = df),
lm(y ~ x + I(x^2), data = df
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