How to get rid of 'NULL' in apply output?-CodePudding

I'm performing permutations and running apply to plot abline or lines from a linear model. But when using apply, I get "NULL" (but it draws the lines). How do I make the "NULL" go away and why is it doing that?

set.seed(12345678)
n = 100; beta0 = 2.5; beta1 = 0.8
x.lm = rnorm(n = n, mean = 10, sd = 1)
err = rnorm(n = n, mean = 0, sd = 1)
# Linear combination 
y.lm = beta0   beta1*x.lm   err
# Make a dataframe of the data 
df.lm = data.frame(x = x.lm, y = y.lm)
par(mar = c(4,4,.5,.5))
# Colour 
b.5 = scales::alpha("black",alpha = .5)
# PLot the data 
plot(y~x, data = df.lm, pch = 19, col = b.5)

# Add permutations
permutate.df =replicate(n = 200, # nperm 
                        expr = data.frame(y = sample(df.lm$y,size = nrow(df.lm), replace = FALSE), x = df.lm$x),
                        simplify = FALSE)
lm.out.perm = mapply(lm, permutate.df)
apply(lm.out.perm,2,function(x) abline(x,col = scales::alpha("orange",.5)))

CodePudding user response：

abline return NULL, usually invisibly. Suggest writing the part from plot onwards like this. Alternately use invisible(Map(...)) in the last line. No packages are used.

plot(y~x, data = df.lm, pch = 19, col = adjustcolor("black", alpha = 0.5))

permuted_dfs <- with(df.lm, replicate(n = 200,
  expr = data.frame(y = sample(y, replace = FALSE), x),
  simplify = FALSE))

fms <- Map(lm, permuted_dfs) # fitted models
junk <- Map(abline, fms, col = adjustcolor("orange", alpha = 0.5))

or as a pipeline if you don't need the intermediate results.

plot(y~x, data = df.lm, pch = 19, col = adjustcolor("black", alpha = 0.5))

df.lm |>
  with(replicate(n = 200, 
         expr = data.frame(y = sample(y, replace = FALSE), x),
         simplify = FALSE)) |>
  Map(f = lm) |>
  Map(f = abline, col = adjustcolor("orange", alpha = 0.5)) |>
  invisible()