Showing 1 - 10 of 14
Longitudinal studies are increasingly common in psychological research. Characterized by repeated measurements, longitudinal designs aim to observe phenomena that change over time. One important question involves identification of the exact point in time when the observed phenomena begin to...
Persistent link: https://www.econbiz.de/10010775995
In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparamet- ric trend and maximum likelihood estimation of the parameters. Convergence and asymptotic properties of the proposed algorithms are...
Persistent link: https://www.econbiz.de/10010324077
Persistent link: https://www.econbiz.de/10008533873
In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparamet- ric trend and maximum likelihood estimation of the parameters. Convergence and asymptotic properties of the proposed algorithms are...
Persistent link: https://www.econbiz.de/10005146733
In this paper we propose a new method to estimate nonparametrically a time varying parameter model when some qualitative information from outside data (e.g. seasonality) is available. In this framework we make two main contributions. First, the resulting estimator is shown to belong to the class...
Persistent link: https://www.econbiz.de/10005187590
Persistent link: https://www.econbiz.de/10005616375
In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparametric trend and maximum likelihood estimation of the parameters. For selecting the bandwidth, the proposal of Beran and Feng (1999) based...
Persistent link: https://www.econbiz.de/10011543365
In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparametric trend and maximum likelihood estimation of the parameters. Convergence and asymptotic properties of the proposed algorithms are...
Persistent link: https://www.econbiz.de/10011544511
In this paper a modified double smoothing bandwidth selector, MDS, based on a new criterion, which combines the plug-in and the double smoothing ideas, is proposed. A self-complete iterative double smoothing rule (_IDS ) is introduced as a pilot method. The asymptotic properties of both_IDS...
Persistent link: https://www.econbiz.de/10011544923
Persistent link: https://www.econbiz.de/10014305525