Forecasting Model Vallidation

Host Institution:

La Trobe University

Title of Seminar:

Forecasting Model Validation

Speaker's Name:

Julia Polak

Speaker's Institution:

Monash University

Time and Date:

Friday 7 October, 2011, 11:00 AM AEST

Seminar Abstract:

Forecasting models play a crucial role in many decision-making areas. Many tools have been developed for model selection and validation (on available data) but only a few exist for answering the question whether the model under the test is still valid for the new observations. This is especially true when one is looking for a quick answer after a small number of extra observations have become available or examines a nonparametric model. We present a method for analyzing the model, which has already been selected, and examining whether its predictive ability is still good enough or the model needs to be reworked. The proposed prediction capability procedure combines the ideas of nonparametric density estimation and principal function data analysis in order to clarify the question whether the new observed data comes from the same expected data generation process or not. If there is not enough evidence that the data generation process has been changed after the model has been selected, there is no reason to believe that the model lost its predictive abilities in the new reality.

Seminar Convenor:

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