Model-Free Prediction and Regression: a Transformation-based Approach to Inference
Neyman Seminar
Nov 23, 2015, 04:00 PM - 05:00 PM | 1011 Evans Hall | Happening As Scheduled
Dimitris Politis, UC San Diego
Prediction has been traditionally approached via a model-based
paradigm, i.e., (a) fit a model
to the data at hand, and (b) use the fitted model to extrapolate/predict future data.
Due to both mathematical and computational constraints, 20th century statistical
practice focused mostly on parametric models.
Fortunately, with the advent of widely accessible powerful computing in the late...