Follow
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
462017
Introducing localgauss, an R package for estimating and visualizing local Gaussian correlation
GD Berentsen, TS Kleppe, DB Tj°stheim
Journal of Statistical Software 56, 1-18, 2014
252014
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
152017
Simulated maximum likelihood estimation of continuous time stochastic volatility models
TS Kleppe, J Yu, HJ Skaug
Maximum Simulated Likelihood Methods and Applications 26, 137-161, 2010
142010
Fitting general stochastic volatility models using Laplace accelerated sequential importance sampling
TS Kleppe, HJ Skaug
Computational Statistics & Data Analysis 56 (11), 3105-3119, 2012
132012
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
Adaptive Step Size Selection for Hessian‐Based Manifold Langevin Samplers
TS Kleppe
Scandinavian Journal of Statistics 43 (3), 788-805, 2016
102016
Trade with endogenous transportation costs: The case of liquefied natural gas
A Oglend, TS Kleppe, P Osmundsen
Energy Economics 59, 138-148, 2016
102016
Efficient importance sampling in mixture frameworks
TS Kleppe, R Liesenfeld
Computational Statistics & Data Analysis 76, 449-463, 2014
10*2014
Maximum likelihood estimation of partially observed diffusion models
TS Kleppe, J Yu, HJ Skaug
Journal of Econometrics 180 (1), 73-80, 2014
92014
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
82018
Dynamically Rescaled Hamiltonian Monte Carlo for Bayesian Hierarchical Models
TS Kleppe
Journal of Computational and Graphical Statistics 28 (3), 493-507, 2019
72019
Estimating the competitive storage model: A simulated likelihood approach
TS Kleppe, A Oglend
Econometrics and statistics 4, 39-56, 2017
72017
Time commitments in LNG shipping and natural gas price convergence
A Oglend, P Osmundsen, TS Kleppe
The Energy Journal 41 (2), 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
An information criterion for automatic gradient tree boosting
B┼S Lunde, TS Kleppe, HJ Skaug
arXiv preprint arXiv:2008.05926, 2020
52020
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
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
Building and Fitting Non‐Gaussian Latent Variable Models via the Moment‐Generating Function
TS Kleppe, HJ Skaug
Scandinavian journal of statistics 35 (4), 664-676, 2008
42008
Numerical path integration for LÚvy driven stochastic differential equations
TS Kleppe
Master’s thesis, NTNU, 2006
42006
The system can't perform the operation now. Try again later.
Articles 1–20