Abstract: The method of logic and probabilistic models constructing for multivariate heterogeneous time series is offered. There are some important properties of these models, e.g. universality. In this paper also discussed the logic and probabilistic models distinctive features in comparison with hidden Markov processes. The early proposed time series forecasting algorithm is tested on applied task.

Keywords: multivariate heterogeneous time series, pattern recognition, classification, deciding functions, logic and probabilistic models.

ACM Classification Keywords: G.3 Probability and statistics: time series analysis, Markov processes, multivariate statistics, nonparametric statistics; G.1.6. Numerical analysis: optimization.

Link:

ПОСТРОЕНИЕ ЛОГИКО-ВЕРОЯТНОСТНЫХ МОДЕЛЕЙ ВРЕМЕННЫХ РЯДОВ С ИСПОЛЬЗОВАНИЕМ ЦЕПЕЙ МАРКОВА

Светлана Неделько

http://foibg.com/ibs_isc/ibs-08/ibs-08-p12.pdf