Abstract
In a previous simulation study, the complexity of neural networks for limited cases of binary and normally-distributed variables based the null distribution of the likelihood ratio statistic and the corresponding chi-square distribution was characterized. This study expands on those results and presents a more general formulation for calculating degrees of freedom.
DOI
10.22237/jmasm/1257034320
Included in
Applied Statistics Commons, Social and Behavioral Sciences Commons, Statistical Theory Commons
