summary.lqm: Summary for an 'lqm' Object

In gforge/lqmm_gforge: Linear Quantile Mixed Models

Description

Summary method for class lqm.

Usage

## S3 method for class 'lqm'
summary(object, method = "boot", alpha = 0.05, covariance = FALSE, ...)

Arguments

object	an object of class lqm
method	specifies the method used to compute standard errors: "boot" for bootstrap (default), "nid" for large sample approximations under nid assumptions.
alpha	significance level.
covariance	logical flag. If TRUE the covariance matrix of the bootstrap estimates is provided.
...	see boot.lqm for additional arguments.

Details

print.summary.lqm formats the coefficients, standard errors, etc. and additionally gives ‘significance stars’.

Value

an object of class summary.lqm. The function summary.lqm computes and returns a list of summary statistics of the fitted linear quantile mixed model given in object, using the components (list elements) from its argument, plus

Cov	the covariance matrix obtained from the bootstrapped estimates (if covariance = TRUE).
tTable	a matrix with estimates, standard errors, etc.

Author(s)

Marco Geraci

Source

The code for the "nid" method has been adapted from the function summary.rq in package quantreg. It depends on the function bandwidth.rq.

Roger Koenker (2016). quantreg: Quantile Regression. R package version 5.29. https://CRAN.R-project.org/package=quantreg

See Also

print.summary.lqm lqm

Examples

set.seed(12356)
n <- 200
p <- 1:3/4
test <- data.frame(x = runif(n,0,1))
test$y <- 30 + test$x + rnorm(n)
fit.lqm <- lqm(y ~ x, data = test, tau = p)
summary(fit.lqm, R = 50)

gforge/lqmm_gforge documentation built on Dec. 20, 2021, 10:42 a.m.