Similar Search Results

Maximum Likelihood Estimation for Generalized Autoregressive Score Models

Blasques, Francisco; Koopman, Siem Jan; Lucas, Andre - Tinbergen Instituut - 2014

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 …

Persistent link: https://www.econbiz.de/10011256845

Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models

Blasques, Francisco; Gorgi, Paolo; Koopman, Siem Jan; … - 2016

. We derive considerably weaker conditions that can be used in practice to ensure the consistency of the maximum likelihood … estimator for a wide class of observation-driven time series models. Our consistency results hold for both correctly specified …

Persistent link: https://www.econbiz.de/10011586697

Maximum likelihood estimation for non-stationary location models with mixture of normal distributions

Blasques, Francisco; van Brummelen, Janneke; Gorgi, Paolo; … - 2022

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

Persistent link: https://www.econbiz.de/10012797266

Maximum Likelihood Estimation for Generalized Autoregressive Score Models

Blasques, Francisco; Koopman, Siem Jan; Lucas, Andre - 2014

Persistent link: https://www.econbiz.de/10010377233

Missing Observations in Observation-Driven Time Series Models

Blasques, Francisco; Gorgi, Paolo; Koopman, Siem Jan - 2018

We argue that existing methods for the treatment of missing observations in observation-driven models lead to inconsistent inference. We provide a formal proof of this inconsistency for a Gaussian model with time-varying mean. A Monte Carlo simulation study supports this theoretical result and...

Persistent link: https://www.econbiz.de/10011819528