data75j4: Simulated data from the OR1 model for p = 0.75 (i.e., 75th...

In bqror: Bayesian Quantile Regression for Ordinal Models

Simulated data from the OR1 model for p = 0.75 (i.e., 75th quantile)

Description

Simulated data from the OR1 model for p = 0.75 (i.e., 75th quantile)

Usage

data(data75j4)

Details

This data contains 500 observations generated from a quantile ordinal model with 4 outcomes at the 75th quantile (i.e., p = 0.75). The model specifics for generating the data are as follows: \beta = (-4, 5, 6), X ~ Unif(0, 1), and \epsilon ~ AL(0, \sigma = 1, p = 0.75). The cut-points (0, 2, 4) are used to classify the continuous values of the dependent variable into 4 categories, which form 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

Rahman, M. A. (2016). “Bayesian Quantile Regression for Ordinal Models.” Bayesian Analysis, 11(1): 1-24. DOI: 10.1214/15-BA939

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 May 31, 2023, 5:19 p.m.