| deplot.lmscreg {VGAM} | R Documentation |
Density Plot for LMS Quantile Regression
Description
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
|
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 |
... |
Graphical parameter that are passed into
|
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$deplot. The list has components
newdata |
The argument |
y |
The argument |
density |
Vector of the density function values evaluated
at |
Note
plotdeplot.lmscreg actually does the plotting.
Author(s)
Thomas W. Yee
References
Yee, T. W. (2004). Quantile regression via vector generalized additive models. Statistics in Medicine, 23, 2295–2315.
See Also
plotdeplot.lmscreg,
qtplot.lmscreg,
lms.bcn,
lms.bcg,
lms.yjn.
Examples
## Not run:
fit <- vgam(BMI ~ s(age, df = c(4, 2)), lms.bcn(zero = 1), bmi.nz)
ygrid <- seq(15, 43, by = 0.25)
deplot(fit, x0 = 20, y = ygrid, xlab = "BMI", col = "green", llwd = 2,
main = "BMI distribution at ages 20 (green), 40 (blue), 60 (red)")
deplot(fit, x0 = 40, y = ygrid, add = TRUE, col = "blue", llwd = 2)
deplot(fit, x0 = 60, y = ygrid, add = TRUE, col = "red", llwd = 2) -> a
names(a@post$deplot)
a@post$deplot$newdata
head(a@post$deplot$y)
head(a@post$deplot$density)
## End(Not run)