R: Visualizing sequences of quantile regression summaries

plot.summary.rqs {quantreg}

R Documentation

Visualizing sequences of quantile regression summaries

Description

A sequence of coefficient estimates for quantile regressions with varying tau parameters is visualized along with associated confidence bands.

Usage

## S3 method for class 'summary.rqs'
plot(x, parm = NULL, level = 0.9, ols = TRUE,
  mfrow = NULL, mar = NULL, ylim = NULL, main = NULL,
  col = gray(c(0, 0.75)), border = NULL, lcol = 2, lty = 1:2,
  cex = 0.5, pch = 20, type = "b", xlab = "", ylab = "", ...)

Arguments

`x`	an object of class `"summary.rqs"` as produce by applying the `summary` method to a `rq` object (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.
`level`	Confidence level of bands. When using the rank based confidence intervals in summary, which is the default method for sample sizes under 1000, you will need to control the level of the intervals by passing the parameter alpha to `summary.rq`, prior to calling `plot.summary.rqs`. Note also that alpha = 1 - level.
`ols`	logical. Should a line for the OLS coefficient and their confidence bands (as estimated by `lm`) be added?
`mfrow, mar, ylim, main`	graphical parameters. Suitable defaults are chosen based on the coefficients to be visualized.
`col`	vector of color specification for `rq` coefficients and the associated confidence polygon.
`border`	color specification for the confidence polygon. By default, the second element of `col` is used.
`lcol, lty`	color and line type specification for OLS coefficients and their confidence bounds.
`cex, pch, type, xlab, ylab, ...`	further graphical parameters passed to `points`.

Details

The plot method for "summary.rqs" objects visualizes the coefficients along with their confidence bands. The bands can be omitted by using the plot method for "rqs" objects directly.

Value

An array with all coefficients visualized (and associated confidence bands) is returned invisibly.

Examples

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

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

[Package quantreg version 5.34 Index]