Estimation of structure by minimum description length
type: Item
instance of: scholarly article
title: Estimation of structure by minimum description length
zbMATH Open document ID: 0541.93008
DOI: 10.1007/BF01599020
author: N. E. Zubov
published in: Circuits, Systems, and Signal Processing
publication date: 1982-01-01T00:00:00Z
review text: This paper proves a theorem which shows that a previously derived minimum description length (MDL) estimation criterion can be used for distinguishing between structures in linear models for vector processes. This is done by considering an extreme case where the data are generated by a system falling outside of the linear space spanned by the coordinate system of the fitted models. The central result of the paper is the proof that in this case the inner product in the third term of the optimum description length: \[ -(1/N)\log P(y/\theta)+(k/2N)\log N+(k/2N)\log(\theta,I_{\theta}(y)\theta) \] grows to infinity with N, while it remains bounded if a model with the same structure as the data generating system is selected. The paper also presents a simple algorithm for estimating the best model, including its structure and the number of its parameters.
Mathematics Subject Classification ID: 93B30
Mathematics Subject Classification ID: 93B10
Mathematics Subject Classification ID: 93B17
Mathematics Subject Classification ID: 93E10
zbMATH DE Number: 3860963
zbMATH Keywords: minimum description length estimation
zbMATH Keywords: linear models
zbMATH Keywords: best model
reviewed by: Spyros G. Tzafestas
MaRDI profile type: Publication
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full work available at URL: https://doi.org/10.1007/bf01599020
OpenAlex ID: W4231506434
description: scientific article; zbMATH DE number 3860963