BLBqr {Brq} | R Documentation |

## Bayesian Lasso Binary quantile regression

### Description

This function implements the idea of Bayesian Lasso Binary quantile regression using a likelihood function that is based on the asymmetric Laplace distribution (Rahim, 2016). The asymmetric Laplace error distribution is written as a scale mixture of normal distributions.

### Usage

`BLBqr(x,y, tau = 0.5, runs = 11000, burn = 1000, thin=1)`

### Arguments

`x` |
Matrix of predictors. |

`y` |
Vector of dependent variable. |

`tau` |
The quantile of interest. Must be between 0 and 1. |

`runs` |
Length of desired Gibbs sampler output. |

`burn` |
Number of Gibbs sampler iterations before output is saved. |

`thin` |
thinning parameter of MCMC draws. |

### Author(s)

Rahim Alhamzawi

[Package

*Brq*version 3.0 Index]