On some nonstationary, nonlinear random processes and their stationary approximations Academic Article uri icon

abstract

  • In this paper our object is to show that a certain class of nonstationary random processes can locally be approximated by stationary processes. The class of processes we are considering includes the time-varying autoregressive conditional heteroscedastic and generalised autoregressive conditional heteroscedastic processes, amongst others. The measure of deviation from stationarity can be expressed as a function of a derivative random process. This derivative process inherits many properties common to stationary processes. We also show that the derivative processes obtained here have alpha-mixing properties. Applied Probability Trust 2006.

published proceedings

  • Advances in Applied Probability

author list (cited authors)

  • Subba Rao, S.

complete list of authors

  • Subba Rao, Suhasini

publication date

  • January 1, 2006 11:11 AM