Description Usage Arguments Details Author(s) See Also Examples
Produces a coefficient profile plot of the quantile
regression coefficient paths for a fitted model of
class “piqr
”.
1 2 3 |
x |
an object of class “ |
xvar |
What is on the X-axis. "norm" plots against the L1-norm of the coefficients, "lambda" against the log-lambda sequence, "objective" against the value of the minimized integrated loss function and "grad" the log-lambda sequence against the gradient. |
label |
If TRUE, label the curves with variable sequence numbers. |
lambda |
a value of lambda in the sequence of the object of class “ |
which |
an optional numerical vector indicating which coefficient(s) to plot. If which = NULL, all coefficients are plotted. |
ask |
logical. If which = NULL and ask = TRUE (the default), you will be asked interactively which coefficients to plot. |
polygon |
ogical. If TRUE, confidence intervals are represented by shaded areas via polygon. Otherwise, dashed lines are used. |
... |
additional graphical parameters, that can include xlim, ylim, xlab, ylab, col, lwd.
See |
A coefficient profile plot is produced.
Gianluca Sottile gianluca.sottile@unipa.ot
piqr
for model fitting; gof.piqr
for the model selection criteria; summary.piqr
and predict.piqr
for model summary and prediction.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | # using simulated data
n <- 1000
x <- runif(n)
qy <- function(p,x){p^2 + x*log(p)}
# true quantile function: Q(p | x) = beta0(p) + beta1(p)*x, with
# beta0(p) = p^2
# beta1(p) = log(p)
y <- qy(runif(n), x) # to generate y, plug uniform p in qy(p,x)
obj <- piqr(y ~ x, formula.p = ~ slp(p,3))
par(mfrow = c(2,2))
plot(obj, xvar="norm")
plot(obj, xvar="lambda")
plot(obj, xvar="objective")
plot(obj, xvar="grad")
# flexible fit with shifted Legendre polynomials
|
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