R help - Sep 2023 - lattice densityplot with weights

density() function in R accepts weights as an input.  Using this
function, one can calculate density and plot it.  Is it possible to
combined these two operations in lattice densityplot()?

mydf <- data.frame(name = "A", x = seq(-2.9, 2.9, by = 0.2), wt
diff(pnorm(seq(-3, 3, by = 0.2))))
mydf <- rbind(mydf, data.frame(name = "B", x = mydf$x + 0.5, wt
mydf$wt))
with(subset(mydf, name == "A"), density(x, weights = wt / sum(wt))
|>
plot(xlim = c(-3, 3.5), xlab = "", main = "Density Plots"))
with(subset(mydf, name == "B"), density(x, weights = wt / sum(wt))
|>
lines(lty = 2, col = 2))
grid()
legend("topright", legend = c("A", "B"), col =
c(1, 2), lty = c(1, 2),
bty = "n")

# I want to do something like this:
# densityplot(~ x, weights = wt, groups = name, data = mydf, type =
c("l", "g"))

Unless I misunderstand...

See ?panel.densityplot

Lattice functions do their work through a host of panel functions,
typically passing their ... arguments to the panel functions.
panel.densityplot has a weights argument.

Cheers,
Bert




On Fri, Sep 29, 2023 at 3:32?AM Naresh Gurbuxani <
naresh_gurbuxani at hotmail.com> wrote:
>
> density() function in R accepts weights as an input.  Using this
> function, one can calculate density and plot it.  Is it possible to
> combined these two operations in lattice densityplot()?
>
> mydf <- data.frame(name = "A", x = seq(-2.9, 2.9, by = 0.2),
wt > diff(pnorm(seq(-3, 3, by = 0.2))))
> mydf <- rbind(mydf, data.frame(name = "B", x = mydf$x + 0.5,
wt > mydf$wt))
> with(subset(mydf, name == "A"), density(x, weights = wt /
sum(wt)) |>
> plot(xlim = c(-3, 3.5), xlab = "", main = "Density
Plots"))
> with(subset(mydf, name == "B"), density(x, weights = wt /
sum(wt)) |>
> lines(lty = 2, col = 2))
> grid()
> legend("topright", legend = c("A", "B"), col
= c(1, 2), lty = c(1, 2),
> bty = "n")
>
> # I want to do something like this:
> # densityplot(~ x, weights = wt, groups = name, data = mydf, type =
c("l",
> "g"))
>
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