ARTIFICIAL NEURAL NETWORKS
8.1 INTRODUCTION
An artificial neural network is a parallel distributed statistical model made up of simple data processing units1 that processes information in currently available data and makes generalizations for future events. Although it is common to use neural network models in a time series context, they can also be used with problems pertaining to cross-section environments.
The inputs and the output(s) of a neural network model can be interpreted as regressors and the regressand, respectively, as in a typical regression model. Estimation of the parameters of a neural network is often called training. This is similar to the parameter estimation in a regression model. The estimation of the parameters of a ...
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