# plot.summary.rqs

##### Visualizing sequences of quantile regression summaries

A sequence of coefficient estimates for quantile
regressions with varying `tau`

parameters is visualized
along with associated confidence bands.

- Keywords
- hplot

##### Usage

```
# S3 method for 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.

##### See Also

##### Examples

```
# NOT RUN {
## 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)
# }
```

*Documentation reproduced from package quantreg, version 5.54, License: GPL (>= 2)*