This function returns fitted values, coefficients and more from a fitted `"hqreg"`

object.

1 2 3 4 5 |

`object` |
Fitted |

`X` |
Matrix of values at which predictions are to be made. Used only for |

`lambda` |
Values of the regularization parameter |

`type` |
Type of prediction. |

`exact` |
If |

`...` |
Not used. Other arguments to predict. |

The object returned depends on type.

Congrui Yi <congrui-yi@uiowa.edu>

Yi, C. and Huang, J. (2016)
*Semismooth Newton Coordinate Descent Algorithm for
Elastic-Net Penalized Huber Loss Regression and Quantile Regression*,
https://arxiv.org/abs/1509.02957

*Journal of Computational and Graphical Statistics, accepted in Nov 2016*

http://www.tandfonline.com/doi/full/10.1080/10618600.2016.1256816

1 2 3 4 5 6 7 8 9 | ```
X = matrix(rnorm(1000*100), 1000, 100)
beta = rnorm(10)
eps = 4*rnorm(1000)
y = drop(X[,1:10] %*% beta + eps)
fit = hqreg(X, y, method = "quantile", tau = 0.7)
predict(fit, X[1:5,], lambda = c(0.05, 0.01))
predict(fit, X[1:5,], lambda = 0.05, exact = TRUE)
predict(fit, X[1:5,], lambda = 0.05, type = "nvars")
coef(fit, lambda = 0.05)
``` |

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