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STICERD Econometrics Seminar Series

Statistical Theory and Algorithms for Machine Learning of Conditional Distribution Functions

Richard Spady (University of Oxford), joint with Sami Stouli, University of Bristol

Thursday 14 February 2019 14:00 - 15:30

32L 4.10, 4th Floor Conference Room, LSE, 32 Lincoln's Inn Fields, London WC2A 3PH

Many of our seminars and public events this year will continue as online seminars or as online and in person. Please check our website listings and Twitter feed @STICERD_LSE for updates.

Unless otherwise specified, current restrictions mean in-person seminars are only open to members of the LSE community (those with a valid LSE ID card).

Those unable to join the seminars in-person are welcome to participate via zoom.


About this event

We propose an algorithm for machine learning of conditional distribution functions for a dependent variable (Y ) with continuous support. The algorithm produces a complete description of the conditional distribution function at all observed points in the covariate (X) space, and provides a similar estimate for other possible covariate values. The descriptions it provides are quite general and are globally valid conditional densities. The algorithm is multi-layered and feed-forward. Each layer has the same statistical interpretation: Layer k takes a vector e(k-1)that is nearly perfectly marginally Gaussian and makes it more marginally Gaussian and more independent of X. It does this by applying a continuous monotonic transformation that varies depending on an observation’s X value. Each layer is estimated by an elastic net regularization of maximum likelihood. We demonstrate Wilks’ phenomenon for the composite algorithm and show how to calculate the algorithm’s effective dimension.

STICERD Econometrics seminars are held on Thursdays in term time at 14.00-15.30, ONLINE, unless specified otherwise.

Seminar organisers: Professor Tai Otsu and Dr. Vassilis Hajivassiliou.

For further information please contact Lubala Chibwe, either by email: l.chibwe@lse.ac.uk.

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This event will take place in 32L 4.10, 4th Floor Conference Room, LSE, 32 Lincoln's Inn Fields, London WC2A 3PH. The building is labelled on the map.

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