Local Prediction Pools

12/14/2021
by   Oscar Oelrich, et al.
0

We propose local prediction pools as a method for combining the predictive distributions of a set of experts whose predictive abilities are believed to vary locally with respect to a set of pooling variables. To estimate the local predictive ability of each expert, we introduce the simple, fast, and interpretable caliper method. Expert pooling weights from the local prediction pool approaches the equal weight solution whenever there is little data on local predictive performance, making the pools robust and adaptive. Local prediction pools are shown to outperform the widely used optimal linear pools in a macroeconomic forecasting evaluation, and in predicting daily bike usage for a bike rental company.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/07/2020

A Locally Adaptive Interpretable Regression

Machine learning models with both good predictability and high interpret...
research
06/22/2021

Predictive multiview embedding

Multiview embedding is a way to model strange attractors that takes adva...
research
07/03/2020

Gaussian Process Regression with Local Explanation

Gaussian process regression (GPR) is a fundamental model used in machine...
research
01/22/2021

Bayesian hierarchical stacking

Stacking is a widely used model averaging technique that yields asymptot...
research
09/08/2022

Hierarchical Graph Pooling is an Effective Citywide Traffic Condition Prediction Model

Accurate traffic conditions prediction provides a solid foundation for v...
research
02/14/2021

From Proper Scoring Rules to Max-Min Optimal Forecast Aggregation

This paper forges a strong connection between two seemingly unrelated fo...
research
02/07/2022

Combining Evidence

The problem of combining the evidence concerning an unknown, contained i...

Please sign up or login with your details

Forgot password? Click here to reset