VGAM (version 1.1-14)

plotqtplot.lmscreg: Quantile Plot for LMS Quantile Regression

Description

Plots the quantiles associated with a LMS quantile regression.

Usage

plotqtplot.lmscreg(fitted.values, object, newdata = NULL,
    percentiles = object@misc$percentiles, lp = NULL,
    add.arg = FALSE, y = if (length(newdata)) FALSE else TRUE,
    spline.fit = FALSE, label = TRUE, size.label = 0.06,
    xlab = NULL, ylab = "",
    pch = par()$pch, pcex = par()$cex, pcol.arg = par()$col,
    xlim = NULL, ylim = NULL,
    llty.arg = par()$lty, lcol.arg = par()$col, llwd.arg = par()$lwd,
    tcol.arg = par()$col, tadj = 1, ...)

Value

The matrix of fitted values.

Details

The above graphical parameters offer some flexibility when plotting the quantiles.

References

Yee, T. W. (2004). Quantile regression via vector generalized additive models. Statistics in Medicine, 23, 2295--2315.

See Also

qtplot.lmscreg.

Examples

if (FALSE) {
fit <- vgam(BMI ~ s(age, df = c(4,2)), lms.bcn(zero = 1), data = bmi.nz)
qtplot(fit)
qtplot(fit, perc = c(25,50,75,95), lcol = "blue", tcol = "blue", llwd = 2)
}