deplot.lmscreg.RdPlots a probability density function associated with a LMS quantile regression.
deplot.lmscreg(object, newdata = NULL, x0, y.arg, show.plot =
TRUE, ...)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.
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.
Numeric. The value of the primary variable at which to make the `slice'.
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.
Logical. Plot it? If FALSE no plot
will be done.
Graphical parameter that are passed into
plotdeplot.lmscreg.
This function calls, e.g., deplot.lms.yjn in order to
compute the density function.
The original object but with a list
placed in the slot post, called
@post$deplot. The list has components
The argument newdata above, or a one-row
data frame constructed out of the x0 argument.
The argument y.arg above.
Vector of the density function values evaluated
at y.arg.
Yee, T. W. (2004). Quantile regression via vector generalized additive models. Statistics in Medicine, 23, 2295–2315.
plotdeplot.lmscreg actually does the plotting.
if (FALSE) { # \dontrun{
fit <- vgam(BMI ~ s(age, df = c(4, 2)), lms.bcn(zero = 1), bmi.nz)
ygrid <- seq(15, 43, by = 0.25)
deplot(fit, x0 = 20, y = ygrid, xlab = "BMI", col = "green", llwd = 2,
main = "BMI distribution at ages 20 (green), 40 (blue), 60 (red)")
deplot(fit, x0 = 40, y = ygrid, add = TRUE, col = "blue", llwd = 2)
deplot(fit, x0 = 60, y = ygrid, add = TRUE, col = "red", llwd = 2) -> a
names(a@post$deplot)
a@post$deplot$newdata
head(a@post$deplot$y)
head(a@post$deplot$density)
} # }