Abstract
Model specification tests are essential tools for evaluating the appropriateness of probability models for estimation and inference. White (Econometrica, 50: 1-25, 1982) proposed that model misspecification could be detected by testing the null hypothesis that the Fisher information matrix (IM) Equality holds by comparing.
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Kashner, T. M., & Kashner, T. M. (2013). New directions in information matrix testing eigenspectrum tests. In Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis: Essays in Honor of Halbert L. White Jr (pp. 145–177). Springer New York. https://doi.org/10.1007/978-1-4614-1653-1_6
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