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A new look at the statistical model identification

Hirotugu Akaike
- 01 Dec 1974 - 
- Vol. 19, Iss: 6, pp 716-723
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TLDR
In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.
Abstract: 
The history of the development of statistical hypothesis testing in time series analysis is reviewed briefly and it is pointed out that the hypothesis testing procedure is not adequately defined as the procedure for statistical model identification. The classical maximum likelihood estimation procedure is reviewed and a new estimate minimum information theoretical criterion (AIC) estimate (MAICE) which is designed for the purpose of statistical identification is introduced. When there are several competing models the MAICE is defined by the model and the maximum likelihood estimates of the parameters which give the minimum of AIC defined by AIC = (-2)log-(maximum likelihood) + 2(number of independently adjusted parameters within the model). MAICE provides a versatile procedure for statistical model identification which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure. The practical utility of MAICE in time series analysis is demonstrated with some numerical examples.

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Modelización de la interferencia
cultivo-malezas, mediante modelos
autorregresivos espaciales, con
validación en un cultivo de lechuga
David Alejandro Jamaica Tenjo
Universidad Nacional de Colombia
Facultad de Ciencias Agrarias, Departamento de Agronomía
Bogotá, Colombia
2019
Modelización de la interferencia
cultivo-malezas, mediante modelos
autorregresivos espaciales, con
validación en un cultivo de lechuga
David Alejandro Jamaica Tenjo
Tesis presentada como requisito parcial para optar al título de:
Doctor en Ciencias Agrarias
Director:
Dr. Enrique Darghan
Codirector:
Dr. José Luis González Andújar
Línea de Investigación en Malherbología
Universidad Nacional de Colombia
Facultad de Ciencias Agrarias, Departamento de Agronomía
Bogotá, Colombia
2019
Maleza:
Cualquier planta cuyas virtudes aún no se han encontrado. (Emerson, 1876), pero que
más virtud, que sobrevivir a todos los intentos humanos por erradicarlas.
A Gabriela, mi hija. La fuente de la fuerza
y la determinación para llevar a cabo esta tesis
A Juliana, mi esposa. Por su infinito apoyo,
paciencia y confianza
Citations
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Journal ArticleDOI

MODELTEST: testing the model of DNA substitution.

David Posada, +1 more
- 01 Jan 1998 - 
TL;DR: The program MODELTEST uses log likelihood scores to establish the model of DNA evolution that best fits the data.
Journal ArticleDOI

On the evaluation of structural equation models

Richard P. Bagozzi, +1 more
- 01 Jan 1988 - 
TL;DR: In this article, structural equation models with latent variables are defined, critiqued, and illustrated, and an overall program for model evaluation is proposed based upon an interpretation of converging and diverging evidence.
Journal ArticleDOI

Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology.

Alan John Camm, +16 more
- 29 Feb 1996 - 
Journal ArticleDOI

Deep learning in neural networks

Jürgen Schmidhuber
- 01 Jan 2015 - 
TL;DR: This historical survey compactly summarizes relevant work, much of it from the previous millennium, review deep supervised learning, unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.
Journal ArticleDOI

jModelTest 2: more models, new heuristics and parallel computing.

Diego Darriba, +4 more
- 01 Aug 2012 - 
TL;DR: jModelTest 2: more models, new heuristics and parallel computing Diego Darriba, Guillermo L. Taboada, Ramón Doallo and David Posada.
References
More filters
Proceedings Article

Information Theory and an Extention of the Maximum Likelihood Principle

H. Akaike
TL;DR: The classical maximum likelihood principle can be considered to be a method of asymptotic realization of an optimum estimate with respect to a very general information theoretic criterion to provide answers to many practical problems of statistical model fitting.
Book ChapterDOI

Information Theory and an Extension of the Maximum Likelihood Principle

Hirotugu Akaike
TL;DR: In this paper, it is shown that the classical maximum likelihood principle can be considered to be a method of asymptotic realization of an optimum estimate with respect to a very general information theoretic criterion.
Book

Information Theory and Statistics

Solomon Kullback

The behavior of maximum likelihood estimates under nonstandard conditions

Peter J. Huber
TL;DR: In this paper, the authors prove consistency and asymptotic normality of maximum likelihood estimators under weaker conditions than usual, such that the true distribution underlying the observations belongs to the parametric family defining the estimator, and the regularity conditions do not involve the second and higher derivatives of the likelihood function.
Book

Information Theory

Robert B. Ash
Frequently Asked Questions (2)
Q1. What are the contributions mentioned in the paper "Modelización de la interferencia cultivo-malezas, mediante modelos autorregresivos espaciales, con validación en un cultivo de lechuga" ?

For this reason, this research proposed and evaluated variants of a spatial autoregressive model that incorporates the assumptions of heterogeneity and dependence. 

estadística espacial, ecología, agronomía y malherbología en la evaluación de los modelos de regresión espacial y en la conformación de nuevas formas de matrices de pesos.