twopartQR: Two part model using Bayesian quantile regression model

Description Usage Arguments Value References Examples

View source: R/twopartQR.R

Description

This function estimates a two part model using a Bayesian quantile regression model to describe the continous part of the conditional distribution. The response variable is assumed to follow a mixed discrete-continuous distribution.

Usage

1
2
3
4
twopartQR(formula, tau = 0.5, data, itNum, thin = 1, betaValue = NULL,
  sigmaValue = 1, vSampleInit = NULL, gammaValue = NULL,
  sigmaGamma = 0.5, link = 1, priorVar = 100, refresh = 100,
  quiet = FALSE)

Arguments

formula

a formula object, with the response on the left of a ~ operator, and the terms, separated by + operators, on the right. If the assumed point mass distribution is at 1, then all values equal to 1 should be replaced by 0.

tau

Quantile of interest.

data

a data.frame from which to find the variables defined in the formula

itNum

Number of iterations.

thin

Thinning parameter.

betaValue

Initial values for the parameter beta for the continuous part.

sigmaValue

Initial value for the scale parameter.

vSampleInit

?

gammaValue

Initial value for the parameter gamma of the discrete part.

sigmaGamma

Tuning parameter for the Metropolis-Hastings step.

link

Integer defining the link function used for the probability model. Default is 1 for the logit link function. If 0, the probit function is used.

priorVar

Value that multiplies a identity matrix in the elicition process of the prior variance of the regression parameters.

refresh

Interval between printing a message during the iteration process. Default is set to 100.

quiet

Logical. If FALSE it will print messages depending on the refresh parameter to show that the chain is updating. If TRUE it will not print messages during the iteration process.

Value

A list with the chains of all parameters of interest.

References

Santos and Bolfarine (2015) - Bayesian quantile regression analysis for continuous data with a discrete component at zero. Preprint. http://arxiv.org/abs/1511.05925

Examples

1
2
3
4
set.seed(1)
data('BrazilElectricity')
modelo2p <- twopartQR(prop_elec/100 ~ population + income_percap, tau=0.5,
 data=BrazilElectricity, itNum=2000, sigmaGamma=2, quiet = TRUE)

brsantos/baquantreg documentation built on Dec. 10, 2018, 1 p.m.