We study the strong consistency and asymptotic normality of the maximum likelihood estimator for a class of time series models driven by the score function of the predictive likelihood. This class of nonlinear dynamic models includes both new and existing observation driven time series models....

The strong consistency and asymptotic normality of the maximum likelihood estimator in observation-driven models usually requires the study of the model both as a filter for the time-varying parameter and as a data generating process (DGP) for observed data. The probabilistic properties of the...

Here we present some preliminary results of a statistical–computational implementation to estimate the wavelet spectrum of unevenly spaced paleoclimate time series by means of the Morlet Weighted Wavelet Z-Transform (MWWZ). A statistical significance test is performed against an ensemble...