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Theory of Probability and Mathematical Statistics



Statistical analysis of conditionally binomial nonlinear regression time series with discrete regressors

Yu. S. Kharin, V. A. Voloshko

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Abstract: The model of conditionally binomial nonlinear regression time series with discrete regressors is considered. A new frequencies-based estimator (FBE) of explicit form is constructed for this model. FBE is shown to be consistent, asymptotically normal, asymptotically effective, and to have less restrictive uniqueness assumptions w. r. t. the classical MLE. A fast recursive algorithm is constructed for FBE re-computation under model extension. Asymptotically optimal Wald test and forecasting

Keywords: Discrete regression time series, discrete regressors, generalized linear model, frequencies-based estimator, asymptotic efficiency, forecasting.

Bibliography:
ed on FBE are developed. Computer experiments on simulated data are performed for FBE.
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