How to plot the sorted coefficients for a lm()/glm() regression model in R?

Question

Let's say I were to execute a regression model in R:

library(data.table)
mtcars = as.data.table(mtcars)
dt = colSums(mtcars)

> dt
     mpg      cyl     disp       hp     drat       wt     qsec       vs 
 642.900  198.000 7383.100 4694.000  115.090  102.952  571.160   14.000 
      am     gear     carb 
  13.000  118.000   90.000 

model = lm(formula=mpg~cyl, data=dt)

The way I would plot the coefficients of this model would be to use the following function, from Extract regression coefficient values

:

plot_coeffs <- function(mlr_model) {
  coeffs <- coefficients(mlr_model)
  mp <- barplot(coeffs, col="#3F97D0", xaxt='n', main="Regression Coefficients")
  lablist <- names(coeffs)
  text(mp, par("usr")[3], labels = lablist, srt = 45, adj = c(1.1,1.1), xpd = TRUE, cex=0.6)
}

plot_coeffs(model)

However, this plot will not plot the coefficients in a sorted manner, eg greatest to least in descending order.

I have tried using order(coeffs) in the above function, but this doesn't seem to work. How does one easily plot the coefficients in decreasing order?

Answer 1

you can order the coefficients and then plot the data:

model = lm(formula=mpg~cyl, data=mtcars)

coeffs <- coefficients(model)
coeffsord <- coeffs[order(coeffs)]

barplot(coeffsord, col="#3F97D0", xaxt='n', main="Regression Coefficients")
text(1:2, labels = names(coeffsord), srt = 45, adj = c(1.1,1.1), xpd = TRUE, cex=0.6)

Answer 2

You can also adapt your function to sort the coefficients:

plot_coeffs_S <- function(mlr_model) {
  coeffs <- sort(coefficients(mlr_model), decreasing = TRUE)  ### changed
  mp <- barplot(coeffs, col="#3F97D0", xaxt='n', main="Regression Coefficients")
  lablist <- names(coeffs)
  text(mp, par("usr")[3], labels = lablist, srt = 45, adj = c(1.1,1.1), xpd = TRUE, cex=0.6)
}