In this paper we consider the non-linear time series model xt=[var epsilon]t([alpha]0+[alpha]1xt-1r[beta]+...+[alpha]pxt-pr[beta])1/r. When r = 2 it is called the [beta]-ARCH(p) model. We examine the geometric ergodicity and the existence of higher-order moments for this model.

This paper proposes an estimation method for superposed spatial point patterns of Neyman–Scott cluster processes of different distance scales and cluster sizes. Unlike the ordinary single Neyman–Scott model, the superposed process of Neyman–Scott models is not identified solely by the...