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Tore Selland Kleppe
Tore Selland Kleppe
Professor of Mathematical Statistics
Verified email at uis.no
Title
Cited by
Cited by
Year
Price dynamics in biological production processes exposed to environmental shocks
F Asche, A Oglend, T Selland Kleppe
American Journal of Agricultural Economics 99 (5), 1246-1264, 2017
602017
Introducing localgauss, an R package for estimating and visualizing local Gaussian correlation
GD Berentsen, TS Kleppe, DB Tjøstheim
Journal of Statistical Software 56, 1-18, 2014
312014
On the behavior of commodity prices when speculative storage is bounded
A Oglend, TS Kleppe
Journal of Economic Dynamics and Control 75, 52-69, 2017
202017
Fitting general stochastic volatility models using Laplace accelerated sequential importance sampling
TS Kleppe, HJ Skaug
Computational Statistics & Data Analysis 56 (11), 3105-3119, 2012
142012
Simulated maximum likelihood estimation of continuous time stochastic volatility models
T Selland Kleppe, J Yu, HJ Skaug
Maximum Simulated Likelihood Methods and Applications, 137-161, 2010
142010
The Gibbs sampler with particle efficient importance sampling for state-space models
O Grothe, TS Kleppe, R Liesenfeld
Econometric Reviews 38 (10), 1152-1175, 2019
122019
Trade with endogenous transportation costs: The case of liquefied natural gas
A Oglend, TS Kleppe, P Osmundsen
Energy Economics 59, 138-148, 2016
122016
Modified Cholesky Riemann manifold Hamiltonian Monte Carlo: exploiting sparsity for fast sampling of high-dimensional targets
TS Kleppe
Statistics and Computing 28, 795-817, 2018
112018
Adaptive Step Size Selection for Hessian‐Based Manifold Langevin Samplers
TS Kleppe
Scandinavian Journal of Statistics 43 (3), 788-805, 2016
112016
Efficient importance sampling in mixture frameworks
TS Kleppe, R Liesenfeld
Computational statistics & data analysis 76, 449-463, 2014
11*2014
Maximum likelihood estimation of partially observed diffusion models
TS Kleppe, J Yu, HJ Skaug
Journal of Econometrics 180 (1), 73-80, 2014
112014
Connecting the dots: numerical randomized Hamiltonian Monte Carlo with state-dependent event rates
TS Kleppe
Journal of Computational and Graphical Statistics 31 (4), 1238-1253, 2022
82022
Estimating the competitive storage model: A simulated likelihood approach
TS Kleppe, A Oglend
Econometrics and statistics 4, 39-56, 2017
82017
An information criterion for automatic gradient tree boosting
BÅS Lunde, TS Kleppe, HJ Skaug
arXiv preprint arXiv:2008.05926, 2020
72020
Dynamically rescaled Hamiltonian Monte Carlo for Bayesian hierarchical models
TS Kleppe
Journal of Computational and Graphical Statistics 28 (3), 493-507, 2019
72019
Time commitments in LNG shipping and natural gas price convergence
A Oglend, P Osmundsen, TS Kleppe
The Energy Journal 41 (2), 29-46, 2020
62020
On the application of improved symplectic integrators in Hamiltonian Monte Carlo
J Mannseth, TS Kleppe, HJ Skaug
Communications in Statistics-Simulation and Computation 47 (2), 500-509, 2018
62018
Can limits‐to‐arbitrage from bounded storage improve commodity term‐structure modeling?
TS Kleppe, A Oglend
Journal of Futures Markets 39 (7), 865-889, 2019
52019
On the application of higher order symplectic integrators in Hamiltonian Monte Carlo
J Mannseth, TS Kleppe, HJ Skaug
arXiv preprint arXiv:1608.07048, 2016
42016
Estimating the GARCH diffusion: simulated maximum likelihood in continuous time
TS Kleppe, J Yu, HJ Skaug
SMU Economics and Statistics Working Paper Series, No. 13-2010, 2010
42010
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