In this paper we consider the problem of determining the law of binary stochastic processes from transition kernels depending on the whole past. These kernels are linear in the past values of the process. They are allowed to assume values close to both 0 and 1, preventing the application of usual results on uniqueness. We give sufficient conditions for uniqueness and non-uniqueness; in the former case a perfect simulation algorithm is also given. © 2013 Springer Science+Business Media New York.
Perfect Simulation of Autoregressive Models with Infinite Memory / DE SANTIS, Emilio; Piccioni, Mauro. - In: JOURNAL OF STATISTICAL PHYSICS. - ISSN 0022-4715. - STAMPA. - 150:6(2013), pp. 1017-1029. [10.1007/s10955-013-0719-7]
Perfect Simulation of Autoregressive Models with Infinite Memory
DE SANTIS, Emilio;PICCIONI, MAURO
2013
Abstract
In this paper we consider the problem of determining the law of binary stochastic processes from transition kernels depending on the whole past. These kernels are linear in the past values of the process. They are allowed to assume values close to both 0 and 1, preventing the application of usual results on uniqueness. We give sufficient conditions for uniqueness and non-uniqueness; in the former case a perfect simulation algorithm is also given. © 2013 Springer Science+Business Media New York.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
