Ludwig-Maximilians-Universität, Institut für Statistik,
Seminar für Statistik und ihre Anwendung in den Wirtschafts- und Sozialwissenschaften

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Artikel:

• Kalus, S., Bothmann, L., Yassouridis, C., Czisch, M., Sämann, P. G., and Fahrmeir, L. (2014): Statistical modelling of time-dependent fMRI activation effects. Submitted to Human Brain Mapping.
  
• Scheipl, F., Kneib, T., Fahrmeir, L. (2013). Penalized likelihood and Bayesian func-tion selection in regression models. AStA (Advances in Statistical Analysis) 97, 349-385.
  
• Konrath, S., Kneib, T., Fahrmeir, L. (2013). Bayesian smoothing, shrinkage and vari-able selection in hazard regression. In: Becker, C., Fried, R., Kuhnt, S. (eds.) Robustness and Complex Data Structures. Festschrift in Honour of Ursula Gather, Springer.
  
• Fahrmeir, L., Kneib, T., Lang, S. (2013). Bayesian Multilevel Models. Ch. 4 in: Scott, M., Simonoff, J., Marx, B. (eds.). The SAGE Handbook of Multilevel Modeling.
• Fenske, N., Fahrmeir, L., Hothorn, T., Rzehak, P., Höhle, M. (2013). Boosting structured additive quantile regression for longitudinal childhood obesity data. Int. J. Biostat. 9(1). DOI 10.1515/ijb-2012-0035.
  
• Kalus, S., Sämann, P., Fahrmeir, L. (2013). Classification of brain activation vial spatial Bayesian variable selection in fMRI regression. Advances in Data Analysis and Classification. DOI 10.1007/s11634-013-0142-6.
  
• Konrath, S., Kneib, T., Fahrmeir, L. (2013). Bayesian smoothing, shrinkage and variable selection in hazard regression. In: Becker, C., Fried, R., Kuhnt, S. (eds.) Robustness and Complex Data Structures. Festschrift in Honour of Ursula Gather, Springer.
• Scheipl, F., Kneib, T., Fahrmeir, L. (2013). Penalized likelihood and Bayesian function selection in regression models. AStA (Advances in Statistical Analysis) 97, 349-385.
• Scheipl, F., Fahrmeir, L., Kneib, T. (2012). Spike-and-slab priors for function selection in structured additive regression models. J. Am. Stat. Assoc. 107, 1518-1532.
  
• Svejdar, V., Kuechenhoff, H., Fahrmeir, L., and Wassermann, J. (2011). External forcing of earthquake swarms at Alpine regions: example from a seismic meteorological network at Mt. Hochstaufen SE-Bavaria. Nonlin. Processes Geophys. 18, 849-860. doi:10.5194/npg-18-849-2011
• Adebayo, S. B., Fahrmeir, L., Seiler, C. and Heumann, C. (2011). Geoadditive latent variable modelling of count data on multiple sexual partnering in Nigeria. Biometrics 64(2), 620-628.
  
• Pyrka, P., Wimmer, V., Fenske, N. Fahrmeir, L. and Schwirtz, A. (2011). Factor Analysis in Performance Diagnostic Data of Competitive Ski Jumpers and Nordic Combined Athletes. Journal of Quantitative Analysis in Sports, 7(3). DOI: 10.2202/1559-0410.1300
• Wimmer, V., Fenske, N., Pyrka, P. and Fahrmeir, L. (2011). Exploring Competition Performance of Decathletes Using Latent Factor Models. Journal of Quantitative Analysis in Sports, 7(4). DOI: 10.2202/1559-0410.1307
• Yahya, W. B., Ulm, K., Fahrmeir, L. and Hapflmeier, A. (2011). k-SS: a sequential feature selection and prediction method in Microarray study. International Journal of Artificial Intelligence, 6, S11.
• Kneib, T., Konrath, S. and Fahrmeir, L. (2011). High-dimensional Structured Additive Regression Models: Bayesian Regularisation, Smoothing and Predictive Performance. Applied Statistics, 60, 51-70.
  
• Kneib, T. and Fahrmeir, L. (2011). A space-time study on forest health. Chapter 10 in: R. Chandler & M. Scott, eds, Statistical Methods for Trend Detection and Analysis in the Environmental Sciences. Wiley & Sons, Hoboken.
• Fahrmeir, L., Kneib, T. and Konrath, S. (2010). Bayesian regularisation in structured additive regression: a unifying perspective on shrinkage, smoothing and predictor selection. Statistics and Computing 20(2), 203-219. DOI: 10.1007/s11222-009-9158-3
• Fahrmeir, L. and Kneib, T. (2009): Discussion on "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations" by Rue, H., Martino, S. and Chopin, N. Journal of the Royal Statistical Society B, 71, 367. DOI:10.1111/j.1467-9868.2008.00700
• Khatab, K. and Fahrmeir, L. (2009). Analysis of Childhood Morbidity with Geoadditive Probit and Latent Variable Model: A Case Study for Egypt. Am. J. Trop. Med. Hyg. 81(1), 114-128.
• Fahrmeir, L. and Kneib, T. (2008). On the identification of trend and correlation in temporal and spatial regression. In: Recent advances in linear models and related areas (eds.: Shalabh, C. Heumann). Physica-Verlag.
• Fahrmeir, L. and Kneib, T. (2008). Propriety of Posteriors in Structured Additive Regression Models: Theory and Empirical Evidence. Journal of Statistical Planning and Inference. DOI:10.1016/j.jspi.2008.05.036
• Kauermann, G., Krivobokova, T., Fahrmeir, L. (2008). Some asymptotic results on generalized penalized spline smoothing. Journal of the Royal Statistical Society, Series B 71(2), 487-503.
• Beyerlein, A., Fahrmeir, L., Mansmann, U., Toschke, M. (2008). Alternative regression models to assess increase in childhood BMI. BMC Medical Research Methodology, 8, 59.
• Ronneberger O., D. Baddeley, F. Scheipl, P.J. Verveer, H. Burkhardt, C. Cremer, L. Fahrmeir, T. Cremer, B. Joffe (2008). Spatial quantitative analysis of fluorescent labeled nuclear structures: Problems, methods, pitfalls. Chromosome Research 16, 523-562.
• Ngianga-Bakwin Kandala, Fahrmeir, L., Klasen S., Priebe J. (2007). Geo-additive models of childhood undernutrition in three Sub-Saharan African countries. To appear in: Population, Space and Place.
• Heim, S., Fahrmeir, L., Eilers, P.H.C., Marx, B.D. (2007). 3d Space varying coefficient models with application to diffusion tensor imaging. Computational Statistics & Data Analysis 51, 6212-6228.
• Fahrmeir, L., Sagerer, F. and Sussmann, G. (2007). Geoadditive regression for analyzing small-scale geographical variability in car insurance. Blätter der Deutschen Gesellschaft für Versicherungsmathematik 28, 47-65.
• Fahrmeir, L. and Raach, A. (2007). A Bayesian semiparametric latent variable model for mixed responses. Psychometrica 72, 327-346.
• Brezger, A. Fahrmeir, L. and Hennerfeind, A. (2007). Adaptive Gaussian Markov Random Fields with Applications in Human Brain Mapping. Applied Statistics (JRSS C) 56, 327-345.
• Smith, M. and Fahrmeir, L. (2007). Spatial Bayesian variable selection with application to functional magnetic resonance imaging. Journal of the American Statistical Association 102, 417-431.
• Fahrmeir, L. and Osuna, L. (2006). Structured Additive Regression for Overdispersed and Zero-Inflated Count Data. Applied Stochastic Models in Business and Industry 22, 351-369.
• Hennerfeind, A., Brezger, A., Fahrmeir, L. (2006). Geoadditive Survival Models. Journal of the American Statistical Association 101, 1065-1075.
• Kneib, T. and Fahrmeir, L. (2006). Structured additive regression for multicategorical space-time data: A mixed model approach. Biometrics 62, 109-118.
• Opgen-Rhein, R., Fahrmeir, L., Strimmer, K. (2005). Inference of demographic history from genealogical trees using reversible jump Markov chain Monte carlo. BMC Evolutionary Biology 5, 6.
• Adebayo, S. and Fahrmeir, L. (2005). Analysing Child Mortality in Nigeria with Geoadditive Survival Models. Statistics in Medicine 24, 709-728.
• Adebayo, S., Fahrmeir, L., Klasen , S (2004). Analyzing infant mortality with geoadditive categorical regression models: a case study for Nigeria. Economics and Human Biology 2, 229–244
• Fahrmeir, L., Kneib, T. and Lang, S. (2004). Penalized Structured Additive Regression for Space-Time Data: a Bayesian Perspective. Statistica Sinica 14, 731-761.
• Heim, S., Hahn, K., Sämann, P., Fahrmeir, L., and Auer, D.P. (2004). On the Assessment of DTI Quality Using Bootstrap Analysis. Magnetic Resonance in Medicine 52, 582-589.
• Fahrmeir, L., Lang, S., Wolff, J. and Bender, S. (2003). Semiparametric Bayesian Time-Space Analysis for Unemployment Duration. Allgemeines Statistisches Archiv 87, 281-307.
• Fahrmeir, L., Lang, S. and Spies, F. (2003). Generalized Geoadditive Models for Insurance Claims Data. Blätter der Deutschen Gesellschaft für Versicherungsmathematik 26, 7-23.
• Lang, S., Adebayo, S., Fahrmeir, L. and Steiner, W. (2003). Bayesian Geoadditive Seemingly Unrelated Regression. Computational Statistics 18, 163-192.
• Smith, M., Pütz, B., Auer, D. and Fahrmeir, L. (2003). Assessing Brain Activity through Spatial Bayesian Variable Selection. NeuroImage 20, 802-815.
• Fahrmeir, L., Henking, A. und Hüls, R. (2002). Methoden zum Vergleich von Scoreverfahren. RiskNEWS 11, 2002, www.rsiknews.de.
• Fahrmeir, L. and Gössl, C. (2002). Semiparametric Bayesian Models for Human Brain Mapping. Statistical Modelling 2, 235-250.
• Fahrmeir, L., Gössl, C. and Hennerfeind, A. (2002). Robust Spatial Smoothing in functional MRI. In: Exploratory Data Analysis in Empirical Research (eds. M. Schwaiger and O. Opitz), p.50-57, Springer, Berlin.
• Gössl, C., Fahrmeir, L., Pütz, F., Auer, L.M. and Auer, D.P. (2002). Fiber tracking from DTI using linear state space models:: Detectability of the pyramidal tract. NeuroImage 16, 378-388.
• Lang, S., Kragler, P., Haybach, G. and Fahrmeir, L. (2002). Bayesian space-time analysis of health insurance data. In: Exploratory Data Analysis in Empirical Research (eds. M. Schwaiger and
  O. Opitz), p.133-140, Springer, Berlin.
• Lang, S., Fronk, E.M. and Fahrmeir, L. (2002). Function Estimation with Locally Adaptive Dynamic Models. Computational Statistics 17, 479-499.
• Becker, U. and Fahrmeir, L. (2001). Bump Hunting for Risk: a New Data Mining Tool and its Applications. Computational Statistics 16, 373-386.
• Biller, C. and Fahrmeir, L. (2001). Bayesian varying-coefficient models using adaptive regression splines. Statistical Modelling 1, 195-211.
• Fahrmeir, L. and Lang, S. (2001). Bayesian semiparametric regression analysis of multicategorical time-space data. Annals of the Institute of Statistical Mathematics 53, 11-30.
• Fahrmeir, L. and Lang, S. (2001). Bayesian inference for generalized additive mixed models based on Markov random field priors. Applied Statistics 50, 201-220.
• Fahrmeir, L. and Mayer J. (2001). Bayesian-type count data models with varying coefficients: estimation and testing in the presence of overdispersion. Appl. Stochastic Models Bus. Ind. 17, 165-179.
• Gössl C., Auer D.P. and Fahrmeir L. (2001). Bayesian Spatiotemporal Inference in Functional Magnetic Resonance Imaging. Biometrics 57, 554-562.
• Gössl C., Fahrmeir, L. and Auer D.P. (2001). Bayesian Modeling of the Hemodynamic Response Function in BOLD fMRI. NeuroImage 14, 140-148.
• Kandala, N.B., Lang, S., Klasen, S. and Fahrmeir, L. (2001). Semi-parametric analysis of the socio-demographic and spatial determinants of undernutrition in two African countries. Research in Official Statistics 4, 81-99.