Michael Eichler

List of publications


  • Empirische Spektralprozesse bei Punktprozessen. Diplomarbeit (in German), Universität Heidelberg, 1992.
  • Wavelet Analysis Based on Sets of Wavelets. MSc-thesis, University of Bath, 1993.
  • Graphical Models in Time Series Analysis. Doctoral thesis, Universität Heidelberg, 1999. [content, .ps.gz, .pdf]


  • M. Eichler (1995). Empirical spectral processes and their applications to stationary point processes. Annals of Applied Probability 5 1161-1176.
  • R. Dahlhaus, M. Eichler, J. Sandkühler (1997). Identification of synaptic connections in neural ensembles by graphical models. Journal of Neuroscience Methods 77 93-107.
  • J. Timmer, M. Lauk, B. Köster, B. Hellwig, S. Häußler, B. Guschlbauer, V. Radt, M. Eichler, G. Deuschl, C.H. Lücking (2000). Cross-spectral analysis of tremor time series. International Journal of Bifurcation and Chaos 10, 2595-2610.
  • M. Eichler, R. Dahlhaus, J. Sandkühler (2003), Partial correlation analysis for the identification of synaptic connections. Biological Cybernetics 89, 289-302.
  • R. Dahlhaus, M. Eichler (2003), Causality and graphical models for time series. In: P. Green, N. Hjort, and S. Richardson (eds.), Highly structured stochastic systems. University Press, Oxford, pp. 115-137.
  • M. Eichler (2005), A graphical approach for evaluating effective connectivity in neural systems. Philosophical Transactions of The Royal Society B 360, 953-967. (previously: Graphical time series modelling in brain imaging)
  • M. Drton and M. Eichler (2006), Maximum likelihood estimation in Gaussian chain graph models under the alternative Markov property. Scandinavian Journal of Statistics 33, 247-257.
  • M. Eichler (2006), On the evaluation of information flow in multivariate systems based on the directed transfer function. Biological Cybernetics 94, 469-482.
  • B. Schelter, M. Winterhalder, M. Eichler, M. Peifer, B. Hellwig, B. Guschlbauer, C.H. Lücking, R. Dahlhaus, J. Timmer (2006), Testing for directed influences in neuroscience using partial directed coherence. Journal of Neuroscience Methods 152, 210-219.
  • M. Eichler (2006), Graphical modelling of dynamic relationships in multivariate time series. In: M. Winterhalder, B. Schelter, J. Timmer (eds), Handbook of Time Series Analysis, Wiley-VCH, Berlin, pp. 335-372. [.pdf]
  • M. Eichler (2006), Fitting graphical interaction models to multivariate time series. Proceedings of the 22nd Conference on Uncertainty in Artificial Intelligence, AUAI Press. [.pdf]
  • M. Eichler (2007), A frequency-domain based test for independence between stationary time series. Metrika 65, 133-157.
  • M. Eichler (2007), Granger-causality and path diagrams for multivariate time series. Journal of Econometrics 137, 334-353.
  • M. Eichler and V. Didelez (2007). Causal reasoning in graphical time series models. In Proceedings of the 23rd Conference on Uncertainty in Artificial Intelligence. [.pdf]
  • B. Wild, M. Eichler, S. Feiler, H.-J. Friederich, M. Hartmann, W. Herzog, S. Zipfel (2007), Dynamic analysis of electronic diary data of obese patients with and without binge eating disorder. Psychotherapy and Psychosomatics 76, 250-252.
  • M. Eichler (2008), Testing nonparametric and semiparametric hypotheses in vector stationary processes. Journal of Multivariate Analysis 99, 968-1009. [DOI:10.1016/j.jmva.2007.06.003]
  • M. Drton, M. Eichler, and T.S. Richardson (2009). Computing maximum likelihood estimates in recursive linear models. Journal of Machinve Learning Research 10, 2329-2348. [arXiv:math.ST/0601631]
  • B. Schelter, J. Timmer, M. Eichler (2009). Assessing the strength of directed influences among neural signals using renormalized partial directed coherence. Journal of Neuroscience Methods 179, 121-130. [DOI:10.1016/j.jneumeth.2009.01.006]
  • L. Sommerlade, M. Eichler, M. Jachan, K. Henschel, J. Timmer, B. Schelter (2009). Estimating causal dependencies in networks of nonlinear stochastic dynamical systems. Physical Review E 80, 051128. [DOI:10.1103/PhysRevE.80.051128]
  • M. Eichler (2009), Causal inference from multivariate time series: What can be learned from Granger causality. In: C. Glymour, W. Wang, D. Westerstahl (eds), Logic, Methodology and Philosophy of Science. Proceedings of the 13th International Congress, College Publications, London. [.pdf]
  • M. Eichler and V. Didelez (2010), On Granger-causality and the effect of interventions in time series. Life time data analysis 16, 3-32. [DOI:10.1007/s10985-009-9143-3]
  • B. Wild, M. Eichler, H.-C. Friederich, M. Hartmann, S. Zipfel, W. Herzog (2010), A graphical vector autoregressive modelling approach to the analysis of electronic diary data. BMC Medical Research Methodology 10:28. [DOI:10.1186/1471-2288-10-28]
  • M. Eichler (2010), Graphical Gaussian modelling of multivariate time series with latent variables. Journal of Machine Learning Research W&CP 9, 193-200. [.pdf]
  • M. Eichler, G. Motta, and R. von Sachs (2011), Fitting dynamic factor models to non-stationary time series. Journal of Econometrics 163, 51-70. [DOI:10.1016/j.jeconom.2010.11.007]
  • M. Eichler (2012), Graphical modelling of multivariate time series. Probability Theory and Related Fields 153, 233-268. [DOI:10.1007/s00440-011-0345-8]
  • M. Eichler (2012). Causal inference in time series analysis. In: C. Berzuini, A.P. Dawid, L. Bernardinelli (eds), Causality: Statistical Perspectives and Applications, Wiley, Chichester. [.pdf]
  • B.D.O. Anderson, M. Deistler, E. Felsenstein, B. Funovits, P. Zadrony, M. Eichler, W. Chen, M. Zamani (2012), Identifiability of regular and singular multivariate autoregressive models from mixed frequency data. In: Proceedings of the 51st IEEE Conference on Decision and Control. [.pdf]
  • M. Eichler and D. Türk (2013), Fitting semiparametric Markov regime-switching models to electricity spot prices. Energy Economics 36, 614-624. [DOI:10.1016/j.eneco.2012.11.013]
  • M. Eichler (2013). Causal inference with multiple time series: principles and problems. Philosophical Transaction of The Royal Society A 371, 20110612. [DOI:10.1098/rsta.2011.0613 or .pdf]
  • R. Ramb, M. Eichler, A. Ing, M. Thiel, C. Weiller, C. Grebogi, Ch. Schwarzbauer, J. Timmer, and B. Schelter (2013), The impact of latent confounders in directed network analysis in neuroscience. Philosophical Transaction of The Royal Society A 371, 20110613. [DOI:10.1098/rsta.2011.0612]
  • M. Eichler, O. Grothe, H. Manner, and D. Türk (2014), Models for short-term forecasting of spike occurrences in Australian electricity markets: a comparitive study. The Journal of Energy Markets 7, 55-81. [.pdf]
  • H. Manner, D. Türk, and M. Eichler (2016), Modeling and forecasting multivariate energy price spikes. Energy Economics 60, 55-65. [DOI:10.1016/j.eneco.2016.10.006]
  • M. Eichler, R. Dahlhaus, and J. Dueck (2017), Graphical modeling for multivariate Hawkes models with nonparametric link functions. Journal of Time Series Analysis 38, 225-242. [DOI:10.1111/jtsa.12213]
  • A. van Delft and M. Eichler (2018), Locally stationary functional time series, Electronic Journal of Statistics 12, 107-170.[DOI:10.1214/17-ejs1384]


  • M. Eichler (2011), A note on separation in mixed graphs, preprint, Maastricht University. [.pdf]
  • M. Eichler (2013), Graphical interaction models for time series: parameter estimation and model selection, preprint, Maastricht University. [.pdf]
  • A. van Delft and M. Eichler (2016), Data-adaptive estimation of time-varying spectral densities, preprint, Maastricht University [arXiv:1512.00825]
  • A. van Delft and M. Eichler (2018), A note on Herglotz’s theorem for time series on function spaces, preprint [arXiv:1801.04262]


  • A. Schmidt, M. Eichler, J. Sandkühler (1998). Identification of direct vs indirect excitatory or inhibitory connections in large neural networks by an extended partial coherence analysis. Pfluegers Arch. Eur. J. Physiol. 435 (Suppl.), R168.
  • M. Eichler (2001), Granger-causality graphs for multivariate time series, Beiträge zur Statistik 64, Universität Heidelberg. [.pdf]
  • R. Dahlhaus and M. Eichler (2001). Time series chain graphs and Granger causality. Proceedings of the ISI2001.
  • R. Dahlhaus and M. Eichler (2002). Causality and graphical models for multivariate time series and point processes. IFMBE Proc 2002 3(2), 1430-1431.
  • S. Feiler, A. Müller, K. Müller, C. Bieber, M. Hartmann, M. Eichler, R. Dahlhaus, W. Eich (2002). Interaktionsgraphen als Methode zur Identifikation von Wirkzusammenhängen im Fibromyalgietherapieprozess. Psychotherapie, Psychosomatik, Medizinische Psychologie 52, 86.
  • B. Wild, M. Eichler, S. Feiler, H.C. Friederich, W. Herzog, S. Zipfel (2006). Prozess-Analyse von elektronischen Tagebuchdaten bei adipösen Patienten mit und ohne Binge-Eating-Disorder. Psychotherapie, Psychosomatik, Medizinische Psychologie 56 [DOI:10.1055/s-2006-934324].
  • M. Eichler (2011). Comment on “Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance” by Kaminski et al. [.pdf]
  • Book review: Reinhard Vontheim: Modelldiagnose in der Bayesschen Inferenz. Lang, Frankfurt am Main, 1999. Statistics in Medicine 20, 163-164 (2001).