plot.rqss {quantreg} | R Documentation

## Plot Method for rqss Objects

### Description

Takes a fitted `rqss` object produced by `rqss()` and plots the component smooth functions that make up the ANOVA decomposition. Since the components "omit the intercept" the estimated intercept is added back in – this facilitates the comparison of quantile fits particularly. For models with a partial linear component or several `qss` components it may be preferable to plot the output of `predict.rqss`. Note that these functions are intended to plot `rqss` objects only, attempting to plot summary.rqss objects just generates a warning message.

### Usage

    ## S3 method for class 'rqss'
    plot(x, rug = TRUE, jit = TRUE, bands = NULL, coverage = 0.95,
    	add = FALSE, shade = TRUE, select = NULL, pages = 0, titles = NULL, ...)
    ## S3 method for class 'qss1'
    plot(x, rug = TRUE, jit = TRUE, add = FALSE, ...)
    ## S3 method for class 'qss2'
    plot(x, render = "contour", ncol = 100, zcol = NULL, ...)
    ## S3 method for class 'summary.rqss'
    plot(x, ...)

### Arguments

`x` | a fitted `rqss` object produced by `rqss()`.
`...` | additional arguments for the plotting algorithm
`rug` | if TRUE, a rugplot for the x-coordinate is plotted
`jit` | if TRUE, the x-values of the rug plot are jittered
`bands` | if TRUE, confidence bands for the smoothed effects are plotted, if "uniform" then uniform bands are plotted, if "both" then both the uniform and the pointwise bands are plotted.
`coverage` | desired coverage probability of confidence bands, if requested
`select` | vector of indices of qss objects to be plotted, by default all
`pages` | number of pages desired for the plots
`render` | a character specifying the rendering for bivariate fits; either `"contour"` (default) or `"rgl"`. The latter requires package rgl.
`add` | if TRUE then add qss curve to existing (usually) scatterplot, otherwise initiate a new plot
`shade` | if TRUE then shade the confidence band
`titles` | title(s) as vector of character strings, by default titles are chosen for each plot as "Effect of CovariateName"
`ncol, zcol` | Only for `render = "rgl"`: number of colors and z values for color construction.

### Details

If `bands == "uniform"` then the bands are uniform bands based on the Hotelling (1939) tube approach. See also Naiman (1986), Johansen and Johnstone (1990), Sun and Loader (1994), and Krivobokova, Kneib, and Claeskens (2009), in particular the computation of the "tube length" is based on the last of these references. If `bands` is non null, and not "uniform" then pointwise bands are returned. Since bands for bivariate components are not (yet) supported, if requested such components will be returned as `NULL`.

### Value

The function produces plots for the ANOVA components as a side effect. For `"qss1"` the `"add = TRUE"` can be used to overplot the fit on a scatterplot. When there are multiple pages required `"par(ask = TRUE)"` is turned on so that the plots may be examined sequentially. If `bands != NULL` then a list with three components for each qss component is returned (invisibly):

`x` | The x coordinates of the confidence bands
`blo` | The y coordinates of the lower confidence curve, if `bands = "both"` then this is a matrix with two columns
`bhi` | The y coordinates of the upper confidence curve, if `bands = "both"` then this is a matrix with two columns

### Author(s)

Roger Koenker

### References

[1] Hotelling, H. (1939): “Tubes and Spheres in $n$-spaces, and a class of statistical problems,” Am J. Math, 61, 440–460.

[2] Johansen, S., and I.M. Johnstone (1990): “Hotelling's Theorem on the Volume of Tubes: Some Illustrations in Simultaneous Inference and Data Analysis,” The Annals of Statistics, 18, 652–684.

[3] Naiman, D. (1986) Conservative confidence bands in curvilinear regression, The Annals of Statistics, 14, 896–906.

[4] Sun, J. and C.R. Loader, (1994) Simultaneous confidence bands for linear regression and smoothing, The Annals of Statistics, 22, 1328–1345.

[5] Krivobokova, T., T. Kneib, and G. Claeskens (2009) Simultaneous Confidence Bands for Penalized Spline Estimators, preprint.

[6] Koenker, R. (2010) Additive Models for Quantile Regression: Model Selection and Confidence Bandaids, preprint.

### See Also

`rqss`

### Examples

    n <- 200
    x <- sort(rchisq(n,4))
    z <- x + rnorm(n)
    y <- log(x)+ .1*(log(x))^2 + log(x)*rnorm(n)/4 + z
    plot(x,y-z)
    fN <- rqss(y~qss(x,constraint="N")+z)
    plot(fN)
    fI <- rqss(y~qss(x,constraint="I")+z)
    plot(fI,  col="blue")
    fCI <- rqss(y~qss(x,constraint="CI")+z)
    plot(fCI, col="red")

    ## A bivariate example
    data(CobarOre)
    fCO <- rqss(z~qss(cbind(x,y),lambda=.08), data = CobarOre)
    plot(fCO)

[Package quantreg version 5.24 Index]