Title :
Asymptotics of Rissanen´s predictive stochastic complexity: from parametric to nonparametric models
Author :
Gerencsér, Laázló
Author_Institution :
Dept. of Electr. Eng., McGill Univ., Montreal, Que., Canada
Abstract :
It is shown that for a wide class of stationary ARMA processes J. Rissanen´s predictive stochastic complexity (1986) is asymptotically equal to the lower bound provided by the Rissanen-Shannon inequality almost surely. An analogous theorem is proved for a more easily computable version of the predictive stochastic complexity based on the recursive estimation of the ARMA parameters
Keywords :
parameter estimation; statistical analysis; stochastic processes; time series; asymptotics; lower bound; nonparametric models; predictive stochastic complexity; recursive parameter estimation; stationary ARMA processes; Automation; Cost function; Difference equations; Polynomials; Predictive models; Recursive estimation; Stochastic processes; Stochastic resonance;
Conference_Titel :
Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
Conference_Location :
Tampa, FL
DOI :
10.1109/CDC.1989.70326
