Please visit my new homepage for an updated list of my publications.

List of publications

Theses:

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]

Articles:

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 Machine 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 (2013), Models for short-term forecasting of spike occurrences in Australian electricity markets: a comparitive study. To appear in: The Journal of Energy Markets. [.pdf]

 
Michael Eichler, February 2014