163 citations · 543 across the 14 of their papers we have counts for
16 papers
Some recent trends in embeddings of time series and dynamic networks
Dag Tjøstheim, Martin Jullum, Anders Løland
We give a review of some recent developments in embeddings of time series and dynamic networks. We start out with traditional principal components and then look at extensions to dy…
Multivariate self-exciting jump processes with applications to financial data
Heidar Eyjolfsson, Dag Tjøstheim
The paper discusses multivariate self- and cross-exciting processes. We define a class of multivariate point processes via their corresponding stochastic intensity processes that a…
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…
Statistical embedding: Beyond principal components
Dag Tjøstheim, Martin Jullum, Anders Løland
There has been an intense recent activity in embedding of very high dimensional and nonlinear data structures, much of it in the data science and machine learning literature. We su…
The Locally Gaussian Partial Correlation
Håkon Otneim, Dag Tjøstheim
It is well known that the dependence structure for jointly Gaussian variables can be fully captured using correlations, and that the conditional dependence structure in the same wa…
Statistical dependence: Beyond Pearson's
Dag Tjøstheim, Håkon Otneim, Bård Støve
Pearson's is the most used measure of statistical dependence. It gives a complete characterization of dependence in the Gaussian case, and it also works well in some non-Gaussi…