Various topics in stochastic processes have been considered in the abstract setting of Riesz spaces, for example martingales, martingale convergence, ergodic theory, AMARTS, Markov processes and mixingales. Here we continue the relaxation of conditional independence begun in the study of mixingales and study mixing processes. The two mixing coefficients which will be considered are the α (strong) and ϕ (uniform) mixing coefficients. We conclude with mixing inequalities for these types of processes. In order to facilitate this development, the study of generalized L 1 and L ∞ spaces begun by Kuo, Labuschagne and Watson will be extended. *
The abstraction of the study of stochastic processes to Banach lattices and vector lattices has received much attention by Grobler, Kuo, Labuschagne, Stoica, Troitsky and Watson over the past fifteen years. By contrast mixing processes have received very little attention. In particular mixingales were generalized to the Riesz space setting in W.-C. Kuo, J.J. Vardy, B.A. Watson, Mixingales on Riesz spaces, J. Math. Anal. Appl., 402 (2013), 731-738. The concepts of strong and uniform mixing as well as related mixing inequalities were extended to this setting in W.-C. Kuo, M.J. Rogans, B.A. Watson, Mixing inequalities in Riesz spaces, J. Math. Anal. Appl., 456 (2017), 992-1004.In the present work we formulate the concept of near-epoch dependence for Riesz space processes and show that if a process is near-epoch dependent and either strong or uniform mixing then the process is a mixingale, giving access to a law of large numbers. The above is applied to autoregessive processes of order 1 in Riesz spaces. *
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