9 citations · 19 across the 6 of their papers we have counts for
6 papers
Subgeometrically ergodic autoregressions with autoregressive conditional heteroskedasticity
Mika Meitz, Pentti Saikkonen
In this paper, we consider subgeometric (specifically, polynomial) ergodicity of univariate nonlinear autoregressions with autoregressive conditional heteroskedasticity (ARCH). The…
Subgeometric ergodicity and -mixing
Mika Meitz, Pentti Saikkonen
It is well known that stationary geometrically ergodic Markov chains are -mixing (absolutely regular) with geometrically decaying mixing coefficients. Furthermore, for initial d…
Subgeometrically ergodic autoregressions
Mika Meitz, Pentti Saikkonen
In this paper we discuss how the notion of subgeometric ergodicity in Markov chain theory can be exploited to study stationarity and ergodicity of nonlinear time series models. Sub…
A mixture autoregressive model based on Student's -distribution
Mika Meitz, Daniel Preve, Pentti Saikkonen
A new mixture autoregressive model based on Student's -distribution is proposed. A key feature of our model is that the conditional -distributions of the component models are…
Stationarity and ergodicity of vector STAR models
Igor L. Kheifets, Pentti J. Saikkonen
Smooth transition autoregressive models are widely used to capture nonlinearities in univariate and multivariate time series. Existence of stationary solution is typically assumed,…
Testing for observation-dependent regime switching in mixture autoregressive models
Mika Meitz, Pentti Saikkonen
Testing for regime switching when the regime switching probabilities are specified either as constants (`mixture models') or are governed by a finite-state Markov chain (`Markov sw…