twopartQR | R Documentation |
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.
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
)
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. |
A list with the chains of all parameters of interest.
Santos and Bolfarine (2015) - Bayesian quantile regression analysis for continuous data with a discrete component at zero. Preprint. http://arxiv.org/abs/1511.05925
set.seed(1)
data('BrazilElectricity')
modelo2p <- twopartQR(prop_elec/100 ~ population + income_percap, tau=0.5,
data=BrazilElectricity, itNum=2000, sigmaGamma=2, quiet = TRUE)
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