Density Plot for LMS Quantile Regression
Plots a probability density function associated with a LMS quantile regression.
deplot.lmscreg(object, newdata = NULL, x0, y.arg, show.plot = TRUE, ...)
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
|
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$deplot. The list has components
newdata |
The argument |
y |
The argument |
density |
Vector of the density function values evaluated at |
plotdeplot.lmscreg actually does the plotting.
Thomas W. Yee
Yee, T. W. (2004). Quantile regression via vector generalized additive models. Statistics in Medicine, 23, 2295–2315.
## Not run:
fit <- vgam(BMI ~ s(age, df = c(4, 2)), fam = lms.bcn(zero = 1), data = bmi.nz)
ygrid <- seq(15, 43, by = 0.25)
deplot(fit, x0 = 20, y = ygrid, xlab = "BMI", col = "green", llwd = 2,
main = "BMI distribution at ages 20 (green), 40 (blue), 60 (red)")
deplot(fit, x0 = 40, y = ygrid, add = TRUE, col = "blue", llwd = 2)
deplot(fit, x0 = 60, y = ygrid, add = TRUE, col = "red", llwd = 2) -> a
names(a@post$deplot)
a@post$deplot$newdata
head(a@post$deplot$y)
head(a@post$deplot$density)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.