cterFit: Fit the continuous threshold expectile regression

In cthreshER: Continuous Threshold Expectile Regression

Description

The grid search algorithm for the continuous threshold expectile regression

Usage

cterFit(y, x, z, tau = 0.5, max.iter = 100, tol = 1e-04)

Arguments

y	A vector of response
x	A scalar covariate with threshold
z	A vector of covariates
tau	the expectile level, 0.5 for default
max.iter	the maximum iteration steps, 100 for default
tol	tolerance value, 1e-4 for default

Value

A list with the elements

coef.est	The estimated regression coefficients with intercept.
threshold.est	The estimated threshold.
coef.se	The estimated standard error of the regression coefficients.
threshold.se	The estimated standard error of the threshold.
iter	The iteration steps.

Author(s)

Feipeng Zhang and Qunhua Li

Examples

## simulated data
ptm <- proc.time()
n <- 200
t0 <- 1.5
bet0 <- c(1, 3, -2, 1)
tau <- 0.3
modtype <- 1
errtype <- 1
dat <- cterSimData(n, bet0, t0, tau, modtype, errtype)
y <- dat[, 1]
x <- dat[, 2]
z <- dat[, 3]
fit <- cterFit(y, x, z, tau)

## The example of Baseball pitcher salary
data(data_bbsalaries)
y <- data_bbsalaries$y
x <- data_bbsalaries$x
z <- NULL
tau <- 0.5
fit <- cterFit(y, x, z, tau)
proc.time() - ptm

cthreshER documentation built on May 2, 2019, 7:58 a.m.