Learn R Programming

VGAM (version 1.1-12)

plotdeplot.lmscreg: Density Plot for LMS Quantile Regression

Description

Plots a probability density function associated with a LMS quantile regression.

Usage

plotdeplot.lmscreg(answer, y.arg, add.arg = FALSE,
    xlab = "", ylab = "density", xlim = NULL, ylim = NULL,
    llty.arg = par()$lty, col.arg = par()$col,
    llwd.arg = par()$lwd, ...)

Value

The list answer, which has components

newdata

The argument newdata above from the argument list of deplot.lmscreg, or a one-row data frame constructed out of the x0 argument.

y

The argument y.arg above.

density

Vector of the density function values evaluated at y.arg.

Arguments

answer

Output from functions of the form deplot.??? where ??? is the name of the VGAM LMS family function, e.g., lms.yjn. See below for details.

y.arg

Numerical vector. The values of the response variable at which to evaluate the density. This should be a grid that is fine enough to ensure the plotted curves are smooth.

add.arg

Logical. Add the density to an existing plot?

xlab, ylab

Caption for the x- and y-axes. See par.

xlim, ylim

Limits of the x- and y-axes. See par.

llty.arg

Line type. See the lty argument of par.

col.arg

Line color. See the col argument of par.

llwd.arg

Line width. See the lwd argument of par.

...

Arguments passed into the plot function when setting up the entire plot. Useful arguments here include main and las.

Author

Thomas W. Yee

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

deplot.lmscreg.

Examples

Run this code
fit <- vgam(BMI ~ s(age, df = c(4,2)), lms.bcn(zero = 1), bmi.nz)
if (FALSE)  y = seq(15, 43, by = 0.25)
deplot(fit, x0 = 20, y = y, xlab = "BMI", col = "green", llwd = 2,
       main = "BMI distribution at ages 20 (green), 40 (blue), 60 (orange)")
deplot(fit, x0 = 40, y = y, add = TRUE, col = "blue", llwd = 2)
deplot(fit, x0 = 60, y = y, add = TRUE, col = "orange", llwd = 2) -> aa

names(aa@post$deplot)
aa@post$deplot$newdata
head(aa@post$deplot$y)
head(aa@post$deplot$density) 

Run the code above in your browser using DataLab