Ludwig Maximilians University, Department of Statistics,
Chair of Statistics and Applied Statistics in Economics, Business
Administration and the Social Sciences
Articles:
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
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
Adebayo, S. B., Fahrmeir, L., Seiler, C. and Heumann, C. (2011).
Geoadditive latent variable modelling of count data on multiple sexual
partnering in Nigeria. Biometrics64(2), 620-628.
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
Computing20(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.
Khatab, K. and Fahrmeir, L. (2009). Analysis of Childhood
Morbidity with Geoadditive Probit and Latent Variable Model: A Case
Study for Egypt.
AmericanJournal of
Tropical Medicine and Hygiene. To appear.
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.
(2008).
Geo-additive models of childhood undernutrition in three Sub-Saharan
African countries. Population,
Space and Place, 14, DOI:
10.1002/psp.524.
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 Association101, 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 Biology5,
6.
Adebayo, S. and Fahrmeir, L. (2005). Analysing Child Mortality in
Nigeria with Geoadditive Survival Models. Statistics in Medicine24, 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 Biology2, 229–244
Fahrmeir, L., Kneib, T. and Lang, S. (2004). Penalized Structured
Additive Regression for Space-Time Data: a Bayesian Perspective. Statistica Sinica14, 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 Medicine52,
582-589.
Fahrmeir, L., Lang, S., Wolff, J. and Bender, S. (2003).
Semiparametric Bayesian Time-Space Analysis of Unemployment Duration. Allgemeines
Statistisches
Archiv87,
281-307.
Fahrmeir, L., Lang, S. and Spies, F. (2003). Generalized
Geoadditive Models for Insurance Claims Data. Blätter der
Deutschen
Gesellschaft für Versicherungsmathematik26, 7-23.
Lang, S., Adebayo, S., Fahrmeir, L. and Steiner, W. (2003).
Bayesian Geoadditive Seemingly Unrelated Regression. Computational
Statistics18, 163-192.
Smith, M., Pütz, B., Auer, D. and Fahrmeir, L. (2003).
Assessing
Brain Activity through Spatial Bayesian Variable Selection. NeuroImage20, 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 Modelling2, 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. NeuroImage16, 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
Statistics17, 479-499.
Becker, U. and Fahrmeir, L. (2001). Bump Hunting for Risk: a New
Data Mining Tool and its Applications. Computational Statistics16, 373-386.
Biller, C. and Fahrmeir, L. (2001). Bayesian varying-coefficient
models using adaptive regression splines. Statistical Modelling1, 195-211.
Fahrmeir, L. and Lang, S. (2001). Bayesian semiparametric
regression analysis of multicategorical time-space data. Annals of
the Institute of Statistical Mathematics53, 11-30.
Fahrmeir, L. and Lang, S. (2001). Bayesian inference for
generalized additive mixed models based on Markov random field priors. Applied
Statistics50, 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. Biometrics57, 554-562.
Gössl C., Fahrmeir, L. and Auer D.P. (2001). Bayesian
Modeling of
the Hemodynamic Response Function in BOLD fMRI. NeuroImage14,
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 Statistics4,
81-99.