C. Diks

发表

Testing the order of discrete Markov chains using surrogate data

M. D. Heyden, C. Diks, B. Hoekstra, 1998 .

Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation

C. Diks, W. Bouten, J. Vrugt, 2005 .

Hydrologic data assimilation using particle Markov chain Monte Carlo simulation: Theory, concepts and applications (online first)

Jasper A. Vrugt, Cees Diks, F BraakterC.J., 2012 .

Nonlinear time series analysis

C. Diks, 1999 .

Financial networks based on Granger causality: A case study

C. Diks, D. Kugiumtzis, A. Papana, 2017 .

Out-of-Sample Comparison of Copula Specifications in Multivariate Density Forecasts

D. Dijk, Dick J. C. van Dijk, C. Diks, 2008 .

Detecting Granger Causality with a Nonparametric Information-based Statistic

C. Diks, H. Fang, 2016 .

UvA-DARE ( Digital Academic Repository ) Simulation study of direct causality measures in multivariate time series

C. Diks, D. Kugiumtzis, A. Papana, 2013 .

Nonparametric Tests for Serial Independence Based on Quadratic Forms

C. Diks, V. Panchenko, 2005 .

Assessment of resampling methods for causality testing: A note on the US inflation behavior

Dimitris Kugiumtzis, Cees Diks, Catherine Kyrtsou, 2017, PloS one.

Critical slowing down as an early warning signal for financial crises?

C. Hommes, C. Diks, Juanxi Wang, 2018, Empirical Economics.

Reversibility as a criterion for discriminating time series

Cees Diks, J. DeGoede, J. C. van Houwelingen, 1995 .

Time reversibility of intracranial human EEG recordings in mesial temporal lobe epilepsy

D. N Velis, Cees Diks, D. Velis, 1996 .

Complex Methods in Economics: An Example of Behavioral Heterogeneity in House Prices∗

Marco van der Leij, Wilko Bolt, Maria Demertzis, 2012 .

Identifying causal relationships in case of non-stationary time series

Dimitris Kugiumtzis, Cees Diks, Angeliki Papana, 2014 .

Comparison of Resampling Techniques for the Non-causality Hypothesis

C. Diks, D. Kugiumtzis, A. Papana, 2014 .

Spatio-temporal chaos: A solvable model

Cees Diks, Floris Takens, F. Takens, 1997 .

UvA-DARE ( Digital Academic Repository ) Transfer Entropy for Nonparametric Granger Causality Detection

C. Diks, H. Fang, 2017 .

Accelerating Markov Chain Monte Carlo Simulation by Differential Evolution with Self-Adaptive Randomized Subspace Sampling

D. Higdon, J. Hyman, C. Diks, 2009 .

Comparing density forecasts in a risk management context

C. Diks, Hao Fang, 2020 .

Comparing the Accuracy of Copula-Based Multivariate Density Forecasts in Selected Regions of Support

Dick J. C. van Dijk, C. Diks, Oleg Sokolinskiy, 2013 .

Nonlinear Granger Causality: Guidelines for Multivariate Analysis: MULTIVARIATE NONLINEAR GRANGER CAUSALITY

C. Diks, M. Wolski, 2016 .

Equivalence and Bifurcations of Finite Order Stochastic Processes

Florian Wagener, F. Wagener, C. Diks, 2005 .

Dynamic interbank network analysis using latent space models

C. Diks, Marco J van der Leij, F. Linardi, 2020 .

Nonlinear Granger Causality: Guidelines for Multivariate Analysis

Marcin Wolski, C. Diks, Cees G. H. Diks, 2013 .

Spatial Correlation Analysis of the Pharmacological Conversion of Sustained Atrial Fibrillation in Conscious Goats by Cibenzoline

M. Allessie, C. Diks, B. Hoekstra, 2000, Archives of physiology and biochemistry.

Assessment of Resampling Methods for Causality Testing

C. Diks, D. Kugiumtzis, A. Papana, 2014 .

Identification of causal relationships in non-stationary time series with an information measure: Evidence for simulated and financial data

C. Diks, D. Kugiumtzis, A. Papana, 2022, Empirical Economics.

Heterogeneity as a natural source of randomness 1

C. Diks, R. V. D. Weide, 2003 .

UvA-DARE (Digital Academic Repository) Functional Structure in Production Networks

C. Diks, P. Sloot, A. Faber, 2021 .

Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails

D. Dijk, C. Diks, V. Panchenko, 2008 .

A generalized CAPM model with asymmetric power distributed errors with an application to portfolio construction

Hao Li, Cees Diks, Te Bao, 2018 .

Detecting Causality in Non-stationary Time Series Using Partial Symbolic Transfer Entropy: Evidence in Financial Data

C. Diks, D. Kugiumtzis, A. Papana, 2015, Computational Economics.

Improved treatment of uncertainty in hydrologic modeling

C. Diks, W. Bouten, J. Vrugt, 2004 .

On the use of distribution-adaptive likelihood functions: Generalized and universal likelihood functions, scoring rules and multi-criteria ranking

C. Diks, J. Vrugt, G. Schoups, 2022, Journal of Hydrology.

New nonparametric measures for instantaneous and granger-causality tail co-dependence

C. Diks, M. Wolski, 2022, Journal of Applied Statistics.

Critical slowing down as an early warning signal for financial crises?

C. Hommes, C. Diks, Juanxi Wang, 2018, Empirical Economics.

Identifying Booms and Busts in House Prices Under Heterogeneous Expectations

Cars Hommes, Cees Diks, Wilko Bolt, 2014, Journal of Economic Dynamics and Control.

Nonparametric Tests for Independence

Cees Diks, C. Diks, 2009, Encyclopedia of Complexity and Systems Science.

Nonlinear analysis of the pharmacological conversion of sustained atrial fibrillation in conscious goats by the class Ic drug cibenzoline.

Maurits A. Allessie, M. Allessie, C. Diks, 1997, Chaos.

Nonlinear Analysis of Epicardial Atrial Electrograms of Electrically Induced Atrial Fibrillation in Man

M. Allessie, C. Diks, B. Hoekstra, 1995, Journal of cardiovascular electrophysiology.

Detecting Causality in Non-stationary Time Series Using Partial Symbolic Transfer Entropy: Evidence in Financial Data

Dimitris Kugiumtzis, Cees Diks, Catherine Kyrtsou, 2016 .

Spatial Correlation Analysis of Atrial Activation Patterns during Sustained Atrial Fibrillation in Conscious Goats

M. Allessie, C. Diks, B. Hoekstra, 2000, Archives of physiology and biochemistry.

Spiral wave dynamics

Cees Diks, J. DeGoede, C. Diks, 1995 .

A new statistic and practical guidelines for nonparametric Granger causality testing

Cees Diks, Valentyn Panchenko, C. Diks, 2006 .

NONPARAMETRIC NONLINEAR CAUSALITY TESTING WITH STEPWISE MULTIVARIATE FILTERING ”

C. Diks, S. Bekiros, 2009 .

Ensemble Bayesian model averaging using Markov Chain Monte Carlo sampling

Martyn P. Clark, Jasper A. Vrugt, Cees Diks, 2008 .

Multi‐objective calibration of forecast ensembles using Bayesian model averaging

Martyn P. Clark, Bruce A. Robinson, Jasper A. Vrugt, 2006 .

A test for symmetries of multivariate probability distributions

Cees Diks, Howell Tong, H. Tong, 1999 .

A Consistent Nonparametric Test for Granger Non-Causality Based on the Transfer Entropy

Hao Fang, Cees Diks, C. Diks, 2020, Entropy.

Improving the Output Quality of Official Statistics Based on Machine Learning Algorithms

Jaap van den Herik, Frank W. Takes, Cees Diks, 2021, Journal of Official Statistics.

The relationship between crude oil spot and futures prices: cointegration, linear and nonlinear causality

Cees Diks, Stelios D. Bekiros, C. Diks, 2008 .

Comparison of point forecast accuracy of model averaging methods in hydrologic applications

Jasper A. Vrugt, Cees Diks, C. Diks, 2010 .

Can a stochastic cusp catastrophe model explain housing market crashes

Cees Diks, C. Diks, Juanxi Wang, 2016 .

Phenomenological and ratio bifurcations of a class of discrete time stochastic processes

F. Wagener, C. Diks, 2011 .

A bifurcation theory for a class of discrete time Markovian stochastic systems

F. Wagener, C. Diks, 2008 .

A Weak Bifurcation Theory for Discrete Time Stochastic Dynamical Systems

Florian Wagener, F. Wagener, C. Diks, 2006 .

Likelihood-based scoring rules for comparing density forecasts in tails

Dick van Dijk, Cees Diks, Valentyn Panchenko, 2011 .

Herding, A-Synchronous Updating and Heterogeneity in Memory in a Cbs

C. Diks, Cees G. H. Diks, Roy van der Weide, 2003 .

A data‐driven supply‐side approach for estimating cross‐border Internet purchases within the European Union

H. J. van den Herik, Frank W. Takes, Q. A. Meertens, 2019, Journal of the Royal Statistical Society: Series A (Statistics in Society).

A Data-Driven Supply-Side Approach for Measuring Cross-Border Internet Purchases

H. J. van den Herik, Frank W. Takes, Q. A. Meertens, 2018, 1805.06930.

A general nonparametric bootstrap test for Granger causality

Cees Diks, J. DeGoede, C. Diks, 2001 .

Informational differences and learning in an asset market with boundedly rational agents

Cees Diks, Pietro Dindo, C. Diks, 2008 .

The nonlinear dynamic relationship of exchange rates: Parametric and nonparametric causality testing

C. Diks, S. Bekiros, 2008 .

On Continuous Beliefs Systems & Herding ∗

C. Diks, R. V. D. Weide, R. Weide, 2003 .

Simulation Study of Direct Causality Measures in Multivariate Time Series

Dimitris Kugiumtzis, Cees Diks, Catherine Kyrtsou, 2013, Entropy.

UvA-DARE ( Digital Academic Repository ) Dynamic Interbank Network Analysis Using Latent Space Models

Fernando Linardi, Cees G. H. Diks, Marco van der Leij, 2022 .

Heterogeneity as a Natural Source of Randomness

C. Diks, Roy van der Weide, 2003 .

Rank-based Entropy Tests for Serial Independence

Cees Diks, Valentyn Panchenko, C. Diks, 2008 .

Weighted Likelihood Ratio Scores for Evaluating Density Forecasts in Tails ∗

D. Dijk, C. Diks, V. Panchenko, 2007 .

Weighted likelihood ratio scores for evaluating forecast densities in tails

D. Dijk, C. Diks, V. Panchenko, 2007 .

Functional Structure in Production Networks

Peter M. A. Sloot, Frank W. Takes, Cees Diks, 2021, Frontiers in Big Data.

Information Cost, Memory Length and Market Instability.

C. Diks, Xindan Li, Chengyao Wu, 2018, Nonlinear Dynamics, Psychology, and Life Sciences.

A Bayesian Approach for Accurate Classification-Based Aggregates pdf

H. Jaap van den Herik, Frank W. Takes, Q. A. Meertens, 2019, SDM.

Transfer Entropy for Nonparametric Granger Causality Detection: An Evaluation of Different Resampling Methods

Hao Fang, Cees Diks, C. Diks, 2017, Entropy.

A Note on the Hiemstra-Jones Test for Granger Non-causality

Cees Diks, Valentyn Panchenko, C. Diks, 2005 .

Redundancies in the Earth's climatological time series

Cees Diks, Manfred Mudelsee, C. Diks, 2000 .

Tests for Serial Independence and Linearity Based on Correlation Integrals

Cees Diks, Sebastiano Manzan, C. Diks, 2002 .

Critical Slowing Down as Early Warning Signals for Financial Crises

C. Hommes, C. Diks, Juanxi Wang, 2015 .

Link-based influence maximization in networks of health promotion professionals

C. Diks, H. Wortelboer, Marco J van der Leij, 2021, PloS one.

The Role of Domestic and Foreign Investors in a Simple Model of Speculative Attacks

C. Diks, D. Botman, 2005, SSRN Electronic Journal.

Detecting differences between delay vector distributions.

C. Diks, J. Degoede, Diks, 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

NCoVaR Granger causality

C. Diks, M. Wolski, 2018 .

Non-linear time series analysis: methods and applications to atrial fibrillation.

M. Allessie, C. Diks, B. Hoekstra, 2001, Annali dell'Istituto superiore di sanita.

Comparing the accuracy of multivariate density forecasts in selected regions of the copula support

D. Dijk, C. Diks, Oleg Sokolinskiy, 2014 .

Noise reduction for functional time series

C. Diks, Bram C W Wouters, 2023, 2307.02154.

Partial Symbolic Transfer Entropy

Dimitris Kugiumtzis, Cees Diks, Catherine Kyrtsou, 2013 .

Methods and Applications

N. Weiskopf, C. Diks, Ranganatha Sitaramb, 2006 .

Predicting Intraday Return Patterns based on Overnight Returns for the US Stock Market

C. Diks, Hao Li, V. Panchenko, 2020 .

The correlation dimension of returns with stochastic volatility

C. Diks, 2003 .

Functional Structure in Production Networks

C. Diks, E. Heemskerk, F. Takes, 2021, Frontiers in Big Data.

Detecting Serial Dependence in Tail Events: A Test Dual to the Bds Test

C. Diks, 2002 .

UvA-DARE (Digital Academic Repository) Assessment of Resampling Methods for Causality Testing: A note on the US Inflation Behavior

C. Diks, A. Papana, Catherine Kyrtsou, 2017 .

Estimating invariants of noisy attractors.

C. Diks, Diks, 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation

C. Diks, Floris Holstege, Bram Wouters, 2023, ArXiv.

Initial Predictions in Learning-to-Forecast Experiment

C. Diks, T. Makarewicz, 2012 .

E&F Chaos: A User Friendly Software Package for Nonlinear Economic Dynamics

Cees Diks, Cars H. Hommes, Valentyn Panchenko, 2008 .

More memory under evolutionary learning may lead to chaos

Cars Hommes, Paolo Zeppini, Cees Diks, 2013 .

Complex Methods in Economics: An Example of Behavioral Heterogeneity in House Prices

W. Bolt, C. Diks, Marco J van der Leij, 2011 .

Methods and Applications

F. Ritort, C. Diks, F Ritort, 2006 .