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.

The lasso procedure is an estimator-shrinkage and variable selection method. This paper shows that there always exists an interval of tuning parameter values such that the corresponding mean squared prediction error for the lasso estimator is smaller than for the ordinary least squares...

Earthquake intensities are modelled as a function of previous activity whose specific form is based on established empirical laws in seismology, but whose parameter values can vary from place to place. This model is used for characterizing regional features of seismic activities in and around...