Skip to content

Quantile and CDF regression (thresholded logistic) via monotonic networks.

Notifications You must be signed in to change notification settings

cottrell/quantile_regression

Repository files navigation

Quantile and CDF Regression Example

Quantile regression objective

$$ J(\tau) = E\left(\rho(\tau, Y - u(\tau, X)|X\right)$$

CDF regression objective

$$ J(y_c) = E\left(\mathbb{1}{Y < y_c} \log v(y_c, X) + (1 - \mathbb{1}{Y < yc}) \log(1 - v(y_x, X)) | X\right)$$

The functions $u$, $v$ must be monotonic in $\tau$ and $y_c$ respectively.

Unconditional distribution of $Y$

Quantile regression

unconditional quantile regression

CDF estimation via logistic regression with monotone network

unconditional cdf regression

Conditional distributional of $Y|X$

Quantile regression

conditional quantile regression

CDF estimation via logistic regression with monotone network

conditional cdf regression

TODO

Do more quantitative error plots etc.

About

Quantile and CDF regression (thresholded logistic) via monotonic networks.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages