lqm.counts: Quantile Regression for Counts

In lqmm: Linear Quantile Mixed Models

Quantile Regression for Counts

Description

This function is used to fit a quantile regression model when the response is a count variable.

Usage

lqm.counts(formula, data, weights = NULL, offset = NULL, contrasts = NULL,
	tau = 0.5, M = 50, zeta = 1e-05, B = 0.999, cn = NULL, alpha = 0.05,
	control = list())

Arguments

formula	an object of class formula: a symbolic description of the model to be fitted.
data	an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which lqm is called.
weights	an optional vector of weights to be used in the fitting process.
offset	an optional offset to be included in the model frame.
contrasts	an optional list. See the contrasts.arg of model.matrix.default.
tau	quantile to be estimated.
M	number of dithered samples.
zeta	small constant (see References).
B	right boundary for uniform random noise U[0,B] to be added to the response variable (see References).
cn	small constant to be passed to F.lqm (see References).
alpha	significance level.
control	list of control parameters of the fitting process. See lqmControl.

Details

A linear quantile regression model if fitted to the log–transformed response. Additional tranformation functions will be implemented. The notation used here follows closely that of Machado and Santos Silva (2005).

Value

an object of class "lqm.counts" containing the following components

tau	the estimated quantile.
theta	regression quantile (on the log–scale).
fitted	predicted quantile (on the response scale).
tTable	coefficients, standard errors, etc.
x	the model matrix.
y	the model response.
offset	offset.
nobs	the number of observations.
M	specified number of dithered samples for standard error estimation.
Mn	actual number of dithered samples used for standard error estimation that gave an invertible D matrix (Machado and Santos Silva, 2005).
term.labels	names for theta.
terms	the terms object used.
rdf	the number of residual degrees of freedom.
InitialPar	starting values for theta.
control	list of control parameters used for optimization (see lqmControl).

Author(s)

Marco Geraci

References

Machado JAF and Santos Silva JMC (2005). Quantiles for counts. Journal of the American Statistical Association, 100(472), 1226–1237.

Examples

n <- 100
x <- runif(n)
test <- data.frame(x = x, y = rpois(n, 2*x))
lqm.counts(y ~ x, data = test, M = 50)

lqmm documentation built on April 6, 2022, 5:09 p.m.