the data generated by our model. Furthermore, we obtain the consistency and asymptotic normality of the maximum likelihood …

its consistency and asymptotic normality. The problem of specifying the optimal value of k  =  k n involved in our …

application of theorems by Meyn and Tweedie [2009]. Under those conditions, the consistency and asymptotic normality of the QMLE …

(2sQML) estimator, this paper shows consistency and asymptotic normality under weak conditions. While second …-order moments are needed for the consistency of the estimated unconditional covariance matrix, the existence of the finite sixth …

robust filtering and forecasting. We provide sufficient conditions for the strong consistency and asymptotic normality of the …

We study the strong consistency and asymptotic normality of the maximum likelihood estimator for a class of time series … processes. We formulate primitive conditions for global identification, invertibility, strong consistency, asymptotic normality …

In this article, consistency and asymptotic normality of the quasi-maximum likelihood estimator (QMLE) in the class of …

dependent errors, are considered for observations over time, space or space-time. Consistency and asymptotic normality of … of many in which consistency of a vector of parameter estimates (which converge at different rates) cannot be established … present a generic consistency result. …

This paper proves consistency and asymptotic normality for the conditional-sum-of-squares (CSS) estimator in fractional … time series models. The models are parametric and quite general. The novelty of the consistency result is that it applies … uniform convergence fails is handled using a truncation argument. The only other consistency proof for such models that …