plot.niqr: Plot Nonlinear Quantile Regression Coefficients

In gianluca-sottile/qrcmNL: Nonlinear Quantile Regression Coefficients Modeling

Description

Plots quantile regression coefficients β(θ, p) as a function of p, based on a fitted model of class “niqr”.

Usage

## S3 method for class 'niqr'
plot(x, conf.int=TRUE, which=NULL, ask=TRUE, ...)

Arguments

x	an object of class “niqr”, typically the result of a call to niqr.
conf.int	logical. If TRUE, asymptotic 95% confidence intervals are added to the plot.
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.
...	additional graphical parameters, that can include xlim, ylim, xlab, ylab, col, lwd. See par.

Author(s)

Gianluca Sottile [e-mail]

See Also

niqr for model fitting; test.fit.niqr for goodness of fit test; summary.niqr and predict.niqr for model summary and prediction.

Examples

  # using simulated data

n <- 1000
x <- runif(n)
fun <- function(theta, p){
  beta0 <- theta[1] + exp(theta[2]*p)
  beta1 <- theta[3] + theta[4]*p
  cbind(beta0, beta1)}
beta <- fun(c(1,1,1,1), runif(n))
y <- beta[, 1] + beta[, 2]*x
model <- niqr(fun=fun, x0=rep(0, 4), X=cbind(1, x), y=y)

par(mfrow=c(1,2))
plot(model, ask=FALSE)

gianluca-sottile/qrcmNL documentation built on May 6, 2019, 6:01 p.m.