Validation and model selection

Abstract

There are two types of simulation models: Demonstration models, essentially existence proofs for phenomena of interest, and Descriptive models, that attempt to track dynamic historical phenomena. Both types require verification. Descriptive models require validation against historical data as well. More broadly, we can think of a process of choosing the “best” of several models. This paper examines three measures of the similarity of two sets of vectors, here time series. The best known but flawed is the Kullback-Leibler information-theoretic construct. A second measure is what I have called the State Similarity Measure. The third measure is a set-theoretic measure of similarity, the Generalized Hartley Metric. For illustration, we use data from a dynamic simulation model of historical brand rivalry.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 32 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.