Unascertained model forecast on poor data with conditions functions in Rⁿ

Abstract

Based on the definitions of poor data, an unascertained model and four axioms, condition functions and range etc. were analyzed then induced second‐order condition function, complemental condition function, connection function and the rule set of some signs concludes with the forecast method, which consists of four theorems and ten inferences, in the condition of data number m (m≥2) in Rⁿ.

Citation

Long, Y. and Boren, D. (2004), "Unascertained model forecast on poor data with conditions functions in Rⁿ", Kybernetes, Vol. 33 No. 2, pp. 315-321. https://doi.org/10.1108/03684920410514274