3 citations · 3 across the 2 of their papers we have counts for
7 papers
agtboost: Adaptive and Automatic Gradient Tree Boosting Computations
Berent Ånund Strømnes Lunde, Tore Selland Kleppe
agtboost is an R package implementing fast gradient tree boosting computations in a manner similar to other established frameworks such as xgboost and LightGBM, but with significan…
An information criterion for automatic gradient tree boosting
Berent Ånund Strømnes Lunde, Tore Selland Kleppe, Hans Julius Skaug
An information theoretic approach to learning the complexity of classification and regression trees and the number of trees in gradient tree boosting is proposed. The optimism (tes…
Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices
Kjartan Kloster Osmundsen, Tore Selland Kleppe, Roman Liesenfeld +1
We propose a state-space model (SSM) for commodity prices that combines the competitive storage model with a stochastic trend. This approach fits into the economic rationality of s…
Analyzing Commodity Futures Using Factor State-Space Models with Wishart Stochastic Volatility
Tore Selland Kleppe, Roman Liesenfeld, Guilherme Valle Moura +1
We propose a factor state-space approach with stochastic volatility to model and forecast the term structure of future contracts on commodities. Our approach builds upon the dynami…
Importance Sampling-based Transport Map Hamiltonian Monte Carlo for Bayesian Hierarchical Models
Kjartan Kloster Osmundsen, Tore Selland Kleppe, Roman Liesenfeld
We propose an importance sampling (IS)-based transport map Hamiltonian Monte Carlo procedure for performing full Bayesian analysis in general nonlinear high-dimensional hierarchica…
Saddlepoint-adjusted inversion of characteristic functions
Berent Å. S. Lunde, Tore S. Kleppe, Hans J. Skaug
For certain types of statistical models, the characteristic function (Fourier transform) is available in closed form, whereas the probability density function has an intractable fo…