| 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 | 67 | 2017 |
| 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 | 33 | 2014 |
| 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 | 21 | 2017 |
| Fitting general stochastic volatility models using Laplace accelerated sequential importance sampling TS Kleppe, HJ Skaug Computational Statistics & Data Analysis 56 (11), 3105-3119, 2012 | 17 | 2012 |
| Adaptive Step Size Selection for Hessian‐Based Manifold Langevin Samplers TS Kleppe Scandinavian Journal of Statistics 43 (3), 788-805, 2016 | 15 | 2016 |
| Trade with endogenous transportation costs: The case of liquefied natural gas A Oglend, TS Kleppe, P Osmundsen Energy Economics 59, 138-148, 2016 | 15 | 2016 |
| 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 | 14 | 2010 |
| 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 | 12 | 2019 |
| 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 | 12 | 2018 |
| 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 | 11 | 2022 |
| Maximum likelihood estimation of partially observed diffusion models TS Kleppe, J Yu, HJ Skaug Journal of Econometrics 180 (1), 73-80, 2014 | 11 | 2014 |
| Time commitments in LNG shipping and natural gas price convergence A Oglend, P Osmundsen, TS Kleppe The Energy Journal 41 (2), 29-46, 2020 | 10 | 2020 |
| Efficient importance sampling in mixture frameworks TS Kleppe, R Liesenfeld Computational statistics & data analysis 76, 449-463, 2014 | 10* | 2014 |
| Dynamically rescaled Hamiltonian Monte Carlo for Bayesian hierarchical models TS Kleppe Journal of Computational and Graphical Statistics 28 (3), 493-507, 2019 | 8 | 2019 |
| Estimating the competitive storage model: A simulated likelihood approach TS Kleppe, A Oglend Econometrics and statistics 4, 39-56, 2017 | 8 | 2017 |
| An information criterion for automatic gradient tree boosting BÅS Lunde, TS Kleppe, HJ Skaug arXiv preprint arXiv:2008.05926, 2020 | 7 | 2020 |
| 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 | 6 | 2018 |
| A risk model of admitting patients with silent SARS-CoV-2 infection to surgery and development of severe postoperative outcomes and death: projections over 24 months for 5 … K Soreide, S Yaqub, J Hallet, JT Kvaløy, TS Kleppe Annals of Surgery 273 (2), 208-216, 2021 | 5 | 2021 |
| 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 | 5 | 2019 |
| Estimating the competitive storage model with stochastic trends in commodity prices KK Osmundsen, TS Kleppe, R Liesenfeld, A Oglend Econometrics 9 (4), 40, 2021 | 4 | 2021 |
