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Structured Additive Regression for Categorical Space–Time Data: A Mixed Model Approach

Kneib, Thomas; Fahrmeir, Ludwig - In: Biometrics 62 (2006) 1, pp. 109-118

Persistent link: https://www.econbiz.de/10010946706

Additive mixed models with Dirichlet process mixture and P-spline priors

Heinzl, Felix; Fahrmeir, Ludwig; Kneib, Thomas - In: AStA Advances in Statistical Analysis 96 (2012) 1, pp. 47-68

Persistent link: https://www.econbiz.de/10010539407

Penalized likelihood and Bayesian function selection in regression models

Scheipl, Fabian; Kneib, Thomas; Fahrmeir, Ludwig - In: AStA Advances in Statistical Analysis 97 (2013) 4, pp. 349-385

Challenging research in various fields has driven a wide range of methodological advances in variable selection for regression models with high-dimensional predictors. In comparison, selection of nonlinear functions in models with additive predictors has been considered only more recently....

Persistent link: https://www.econbiz.de/10010698292

Geoadditive Latent Variable Modeling of Count Data on Multiple Sexual Partnering in Nigeria

Adebayo, Samson B.; Fahrmeir, Ludwig; Seiler, Christian; … - In: Biometrics 67 (2011) 2, pp. 620-628

Persistent link: https://www.econbiz.de/10010946911

An Application of Isotonic Longitudinal Marginal Regression to Monitoring the Healing Process

Fahrmeir, Ludwig; Gieger, Christian; Heumann, Christian - In: Biometrics 55 (1999) 3, pp. 951-956

Persistent link: https://www.econbiz.de/10010947076

Handbook of Statistics 21: Stochastic Processes: Modelling and Simulation

Fahrmeir, Ludwig - In: Biometrics 62 (2006) 3, pp. 943-944

Persistent link: https://www.econbiz.de/10010948308

Variable Selection and Model Choice in Geoadditive Regression Models

Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard - In: Biometrics 65 (2009) 2, pp. 626-634

Persistent link: https://www.econbiz.de/10010947837

Semiparametric multinomial logit models for analysing consumer choice behaviour

Kneib, Thomas; Baumgartner, Bernhard; Steiner, Winfried - In: AStA Advances in Statistical Analysis 91 (2007) 3, pp. 225-244

Persistent link: https://www.econbiz.de/10005598069