Density Plot for LMS Quantile Regression

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

Usage

deplot.lmscreg(object, newdata = NULL, x0, y.arg, show.plot =
               TRUE, ...)

Arguments

object

A VGAM quantile regression model, i.e., an object produced by modelling functions such as vglm and vgam with a family function beginning with "lms.", e.g., lms.yjn.

newdata

Optional data frame containing secondary variables such as sex. It should have a maximum of one row. The default is to use the original data.

x0

Numeric. The value of the primary variable at which to make the `slice'.

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.

show.plot

Logical. Plot it? If FALSE no plot will be done.

...

Graphical parameter that are passed into plotdeplot.lmscreg.

Details

This function calls, e.g., deplot.lms.yjn in order to compute the density function.

Value

The original object but with a list placed in the slot post, called @post$deplot. The list has components

newdata: The argument newdata above, 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.

References

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

Author

Thomas W. Yee

Note

plotdeplot.lmscreg actually does the plotting.

Examples

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

names(a@post$deplot)
a@post$deplot$newdata
head(a@post$deplot$y)
head(a@post$deplot$density)
} # }