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