We propose a state space model with Markov switching, whose regimes are associated with the model parameters and regime transition probabilities are modeled using wavelets. The estimation is based on the maximum likelihood method using the EM algorithm and a bootstrap method is proposed in order...

We propose a state space model with Markov switching, whose regimes are associated with the model parameters and regime transition probabilities are modeled using wavelets. The estimation is based on the maximum likelihood method using the EM algorithm and a bootstrap method is proposed in order...

In this paper, we consider estimating copulas for time series, under mixing conditions, using wavelet expansions. The proposed estimators are based on estimators of densities and distribution functions. Some statistical properties of the estimators are derived and their performance assessed via...

The overall test for lack of fit for time series models proposed by Box and Pierce (1970) and Ljung and Box (1978) is modified to include the case when observations are missing. The missing data mechanism considered here is general and nonparametric.