9 citations · 12 across the 5 of their papers we have counts for
5 papers
Computational issues in parameter estimation for hidden Markov models with Template Model Builder
Timothée Bacri, Geir D. Berentsen, Jan Bulla +1
A popular way to estimate the parameters of a hidden Markov model (HMM) is direct numerical maximization (DNM) of the (log-)likelihood function. The advantages of employing the TMB…
A gentle tutorial on accelerated parameter and confidence interval estimation for hidden Markov models using Template Model Builder
Timothée Bacri, Geir D. Berentsen, Jan Bulla +1
A very common way to estimate the parameters of a hidden Markov model (HMM) is the relatively straightforward computation of maximum likelihood (ML) estimates. For this task, most…
Portfolio Allocation under Asymmetric Dependence in Asset Returns using Local Gaussian Correlations
Anders D. Sleire, Bård Støve, Håkon Otneim +3
It is well known that there are asymmetric dependence structures between financial returns. In this paper we use a new nonparametric measure of local dependence, the local Gaussian…
Heritability curves: a local measure of heritability
Geir D. Berentsen, Francesca Azzolini, Hans J. Skaug +2
This paper introduces a new measure of heritability which relaxes the classical assumption that the degree of heritability of a continuous trait can be summarized by a single numbe…
Modelling corporate defaults: A Markov-switching Poisson log-linear autoregressive model
Geir D. Berentsen, Jan Bulla, Antonello Maruotti +1
This article extends the autoregressive count time series model class by allowing for a model with regimes, that is, some of the parameters in the model depend on the state of an u…