- <Source Information> Lijuan Huo and Jin Seo Cho (2020): Entropy, 22, 1294.
- <Abstract> This paper studies the extreme learning machine (ELM) applied to the Wald test statistic for model specification of the conditional mean, which we call the WELM testing procedure. The omnibus test statistics available in the literature weakly converge to a Gaussian stochastic process under the null that the model is correct, and it makes their application inconvenient. In contrast, the WELM testing procedure is straightforwardly applicable when detecting model misspecification. We apply the WELM testing procedure to the sequential testing procedure formed by a set of polynomial models and estimate an approximate conditional expectation by this. We conduct extensive Monte Carlo experiments and evaluate the performance of the sequential WELM testing procedure and verify that it consistently estimates the most parsimonious conditional mean, when the set of the polynomial models contains a correctly specified model. Otherwise, it consistently rejects all the models in the set.