Quantile Plot for LMS Quantile Regression
Plots the quantiles associated with a LMS quantile regression.
plotqtplot.lmscreg(fitted.values, object, newdata = NULL, percentiles = object@misc$percentiles, lp = NULL, add.arg = FALSE, y = if (length(newdata)) FALSE else TRUE, spline.fit = FALSE, label = TRUE, size.label = 0.06, xlab = NULL, ylab = "", pch = par()$pch, pcex = par()$cex, pcol.arg = par()$col, xlim = NULL, ylim = NULL, llty.arg = par()$lty, lcol.arg = par()$col, llwd.arg = par()$lwd, tcol.arg = par()$col, tadj = 1, ...)
fitted.values |
Matrix of fitted values. |
object |
A VGAM quantile regression model, i.e.,
an object produced by modelling functions such as |
newdata |
Data frame at which predictions are made. By default, the original data are used. |
percentiles |
Numerical vector with values between 0 and 100 that specify the percentiles (quantiles). The default is to use the percentiles when fitting the model. For example, the value 50 corresponds to the median. |
lp |
Length of |
add.arg |
Logical. Add the quantiles to an existing plot? |
y |
Logical. Add the response as points to the plot? |
spline.fit |
Logical. Add a spline curve to the plot? |
label |
Logical. Add the percentiles (as text) to the plot? |
size.label |
Numeric. How much room to leave at the RHS for the label. It is in percent (of the range of the primary variable). |
xlab |
Caption for the x-axis. See |
ylab |
Caption for the x-axis. See |
pch |
Plotting character. See |
pcex |
Character expansion of the points.
See |
pcol.arg |
Color of the points.
See the |
xlim |
Limits of the x-axis. See |
ylim |
Limits of the y-axis. See |
llty.arg |
Line type. Line type.
See the |
lcol.arg |
Color of the lines.
See the |
llwd.arg |
Line width.
See the |
tcol.arg |
Color of the text
(if |
tadj |
Text justification.
See the |
... |
Arguments passed into the |
The above graphical parameters offer some flexibility when plotting the quantiles.
The matrix of fitted values.
While the graphical arguments of this function are useful to the user, this function should not be called directly.
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)), lms.bcn(zero = 1), data = bmi.nz) qtplot(fit) qtplot(fit, perc = c(25,50,75,95), lcol = "blue", tcol = "blue", llwd = 2) ## End(Not run)
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