mqr {alqrfe} | R Documentation |

## multiple penalized quantile regression

### Description

Estimate QR for several taus

### Usage

```
mqr(x, y, subj, tau = 1:9/10, method = "qr", ngrid = 20, inf = 1e-08, digt = 4)
```

### Arguments

`x` |
Numeric matrix, covariates |

`y` |
Numeric vector, outcome. |

`subj` |
Numeric vector, identifies the unit to which the observation belongs. |

`tau` |
Numeric vector, identifies the percentiles. |

`method` |
Factor, "qr" quantile regression, "qrfe" quantile regression with fixed effects, "lqrfe" Lasso quantile regression with fixed effects, "alqr" adaptive Lasso quantile regression with fixed effects. |

`ngrid` |
Numeric scalar greater than one, number of BIC to test. |

`inf` |
Numeric scalar, internal value, small value. |

`digt` |
Numeric scalar, internal value greater than one, define "zero" coefficient. |

### Value

Beta Numeric array, with three dimmensions: 1) tau, 2) coef., lower bound, upper bound, 3) exploratory variables.

### Examples

```
n = 10
m = 5
d = 4
N = n*m
L = N*d
x = matrix(rnorm(L), ncol=d, nrow=N)
subj = rep(1:n, each=m)
alpha = rnorm(n)
beta = rnorm(d)
eps = rnorm(N)
y = x %*% beta + matrix(rep(alpha, each=m) + eps)
y = as.vector(y)
Beta = mqr(x,y,subj,tau=1:9/10, method="qr", ngrid = 10)
Beta
```

[Package

*alqrfe*version 1.1 Index]