plot.rqs: Visualizing sequences of quantile regressions

Description

A sequence of coefficient estimates for quantile regressions with varying tau parameters is visualized.

Usage

# S3 method for rqs
plot(x, parm = NULL, ols = TRUE,
  mfrow = NULL, mar = NULL, ylim = NULL, main = NULL, col = 1:2, lty = 1:2,
  cex = 0.5, pch = 20, type = "b", xlab = "", ylab = "", ...)

Value

A matrix with all coefficients visualized is returned invisibly.

Arguments

x: an object of class "rqs" as produce by rq (with a vector of tau values).
parm: a specification of which parameters are to be plotted, either a vector of numbers or a vector of names. By default, all parameters are considered.
ols: logical. Should a line for the OLS coefficient (as estimated by lm) be added?
mfrow, mar, ylim, main: graphical parameters. Suitable defaults are chosen based on the coefficients to be visualized.
col, lty: graphical parameters. For each parameter, the first element corresponds to the rq coefficients and the second to the lm coefficients.
cex, pch, type, xlab, ylab, ...: further graphical parameters passed.

Details

The plot method for "rqs" objects visualizes the coefficients only, confidence bands can be added by using the plot method for the associated "summary.rqs" object.

Examples

Run this code

## fit Engel models (in levels) for tau = 0.1, ..., 0.9
data("engel")
fm <- rq(foodexp ~ income, data = engel, tau = 1:9/10)

## visualizations
plot(fm)
plot(fm, parm = 2, mar = c(5.1, 4.1, 2.1, 2.1), main = "", xlab = "tau", 
  ylab = "income coefficient", cex = 1, pch = 19)