| Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling JA Vrugt, CJF ter Braak, CGH Diks, BA Robinson, JM Hyman, D Higdon International journal of nonlinear sciences and numerical simulation 10 (3 …, 2009 | 1252 | 2009 |
| A new statistic and practical guidelines for nonparametric Granger causality testing C Diks, V Panchenko Journal of Economic Dynamics and Control 30 (9-10), 1647-1669, 2006 | 1140 | 2006 |
| Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation JA Vrugt, CGH Diks, HV Gupta, W Bouten, JM Verstraten Water resources research 41 (1), 2005 | 693 | 2005 |
| The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality SD Bekiros, CGH Diks Energy Economics 30 (5), 2673-2685, 2008 | 476 | 2008 |
| A note on the Hiemstra-Jones test for Granger non-causality C Diks, V Panchenko Studies in nonlinear dynamics & econometrics 9 (2), 2005 | 312 | 2005 |
| Hydrologic data assimilation using particle Markov chain Monte Carlo simulation: Theory, concepts and applications JA Vrugt, CJF ter Braak, CGH Diks, G Schoups Advances in Water Resources 51, 457-478, 2013 | 223 | 2013 |
| Reversibility as a criterion for discriminating time series C Diks, JC Van Houwelingen, F Takens, J DeGoede Physics Letters A 201 (2-3), 221-228, 1995 | 220 | 1995 |
| Nonlinear time series analysis: methods and applications C Diks World Scientific, 1999 | 211 | 1999 |
| Likelihood-based scoring rules for comparing density forecasts in tails C Diks, V Panchenko, D Van Dijk Journal of Econometrics 163 (2), 215-230, 2011 | 193 | 2011 |
| Comparison of point forecast accuracy of model averaging methods in hydrologic applications CGH Diks, JA Vrugt Stochastic Environmental Research and Risk Assessment 24, 809-820, 2010 | 193 | 2010 |
| Detecting differences between delay vector distributions C Diks, WR Van Zwet, F Takens, J DeGoede Physical Review E 53 (3), 2169, 1996 | 163 | 1996 |
| Ensemble Bayesian model averaging using Markov chain Monte Carlo sampling JA Vrugt, CGH Diks, MP Clark Environmental fluid mechanics 8, 579-595, 2008 | 158 | 2008 |
| Efficient implementation of the Gaussian kernel algorithm in estimating invariants and noise level from noisy time series data D Yu, M Small, RG Harrison, C Diks Physical Review E 61 (4), 3750, 2000 | 127 | 2000 |
| Herding, a-synchronous updating and heterogeneity in memory in a CBS C Diks, R Van Der Weide Journal of Economic dynamics and control 29 (4), 741-763, 2005 | 117 | 2005 |
| Estimating invariants of noisy attractors C Diks Physical review E 53 (5), R4263, 1996 | 114 | 1996 |
| Nonlinear analysis of epicardial atrial electrograms of electrically induced atrial fibrillation in man BPT Hoekstra, CGH Diks, MA Allessie, J De Goedb Journal of cardiovascular electrophysiology 6 (6), 419-440, 1995 | 105 | 1995 |
| Critical slowing down as an early warning signal for financial crises? C Diks, C Hommes, J Wang Empirical Economics 57, 1201-1228, 2019 | 102 | 2019 |
| Simulation study of direct causality measures in multivariate time series A Papana, C Kyrtsou, D Kugiumtzis, C Diks Entropy 15 (7), 2635-2661, 2013 | 100 | 2013 |
| Financial networks based on Granger causality: A case study A Papana, C Kyrtsou, D Kugiumtzis, C Diks Physica A: Statistical Mechanics and its Applications 482, 65-73, 2017 | 90 | 2017 |
| Multi‐objective calibration of forecast ensembles using Bayesian model averaging JA Vrugt, MP Clark, CGH Diks, Q Duan, BA Robinson Geophysical Research Letters 33 (19), 2006 | 89 | 2006 |
