In this article we examine how model selection in neural networks can be guided by statistical procedures such as hypotheses tests, information criteria and cross validation. The application of these methods in neural network models is discussed, paying attention especially to the identification...

In this paper, we propose a new Empirical Information Criterion (EIC) for model selection which penalizes the likelihood of the data by a function of the number of parameters in the model. It is designed to be used where there are a large number of time series to be forecast. However, a...

A new method, called relevant transformation of the inputs network approach (RETINA) is proposed as a tool for model building and selection. It is designed to improve on some of the shortcomings of neural networks. RETINA has the flexibility of neural network models, the concavity of the...

In Perez-Amaral, Gallo, and White (2003), the authors proposed an automatic predictive modelling tool called Relevant Transformation of the Inputs Network Approach (RETINA). It is designed to embody flexibility (using nonlinear transformations of the predictors of interest), selective search...

In this article we examine how model selection in neural networks can be guided by statistical procedures such as hypotheses tests, information criteria and cross validation. The application of these methods in neural network models is discussed, paying attention especially to the identification...

This paper addresses the growing gulf between traditional macroeconometrics and the increasingly dominant preference among macroeconomists to use DSGE models and to estimate them using Bayesian estimation with strong priors but not to test them as they are likely to fail conventional statistical...

Schwarz. In this paper I evaluate the predictive ability of the Akaike and Schwarz information criteria using autoregressive integrated moving average models, with sectoral data of Chilean GDP. In terms of root mean square error, and after the estimation of more than a million models, the...

Tests for relative predictive accuracy have become a widespread addendum to forecast comparisons. Many empirical research reports conclude that the difference between the entertained forecasting models is 'insignificant'. This paper collects arguments that cast doubt on the usefulness of...