data50j3: Simulated data from OR2 model for p = 0.5 (i.e., 50th...

In bqror: Bayesian Quantile Regression for Ordinal Models

Simulated data from OR2 model for p = 0.5 (i.e., 50th quantile)

Description

Simulated data from OR2 model for p = 0.5 (i.e., 50th quantile)

Usage

data(data50j3)

Details

This data contains 500 observations generated from a quantile ordinal model with 3 outcomes at the 50th quantile (i.e., p = 0.5). The model specifics for generating the data are as follows: β = (-4, 6, 5), X ~ Unif(0, 1), and ε ~ AL(0, σ = 1, p = 0.5). The cut-points (0, 3) are used to classify the continuous values of the dependent variable into 3 categories, which forms the ordinal outcomes.

Value

Returns a list with components

• x: a matrix of covariates, including a column of ones.

• y: a column vector of ordinal outcomes.

References

Kozumi, H., and Kobayashi, G. (2011). “Gibbs Sampling Methods for Bayesian Quantile Regression.” Journal of Statistical Computation and Simulation, 81(11), 1565–1578. DOI: 10.1080/00949655.2010.496117

Yu, K., and Zhang, J. (2005). “A Three-Parameter Asymmetric Laplace Distribution.” Communications in Statistics - Theory and Methods, 34(9-10), 1867-1879. DOI: 10.1080/03610920500199018

See Also

mvrnorm, Asymmetric Laplace Distribution

bqror documentation built on July 6, 2022, 5:07 p.m.