summary.lqm: Summary for an 'lqm' Object

Description Usage Arguments Details Value Author(s) Source See Also Examples

View source: R/lqm.R

Description

Summary method for class lqm.

Usage

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## 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 (2015). quantreg: Quantile Regression. R package version 5.19. http://CRAN.R-project.org/package=quantreg

See Also

print.summary.lqm lqm

Examples

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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)

lqmm documentation built on May 30, 2017, 1:31 a.m.

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