### Abstract

Lingua originale | English |
---|---|

pagine (da-a) | 1557-1569 |

Numero di pagine | 0 |

Rivista | Journal of Statistical Computation and Simulation |

Volume | 82 |

Stato di pubblicazione | Published - 2012 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Statistics and Probability
- Applied Mathematics
- Statistics, Probability and Uncertainty
- Modelling and Simulation

### Cita questo

**Quantile regression via iterative least squares computations.** / Muggeo, Vito Michele Rosario; Sciandra, Mariangela; Augugliaro, Luigi.

Risultato della ricerca: Article

*Journal of Statistical Computation and Simulation*, vol. 82, pagg. 1557-1569.

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TY - JOUR

T1 - Quantile regression via iterative least squares computations

AU - Muggeo, Vito Michele Rosario

AU - Sciandra, Mariangela

AU - Augugliaro, Luigi

PY - 2012

Y1 - 2012

N2 - We present an estimating framework for quantile regression where the usual L1-norm objective function is replaced by its smooth parametric approximation. An exact path-following algorithm is derived, leading to the well-known ‘basic’ solutions interpolating exactly a number of observations equal to the number of parameters being estimated. We discuss briefly possible practical implications of the proposed approach, such as early stopping for large data sets, confidence intervals, and additional topics for future research.

AB - We present an estimating framework for quantile regression where the usual L1-norm objective function is replaced by its smooth parametric approximation. An exact path-following algorithm is derived, leading to the well-known ‘basic’ solutions interpolating exactly a number of observations equal to the number of parameters being estimated. We discuss briefly possible practical implications of the proposed approach, such as early stopping for large data sets, confidence intervals, and additional topics for future research.

KW - quantile regression; least squares; smooth approximation

UR - http://hdl.handle.net/10447/62348

M3 - Article

VL - 82

SP - 1557

EP - 1569

JO - Journal of Statistical Computation and Simulation

JF - Journal of Statistical Computation and Simulation

SN - 0094-9655

ER -