138 citations · 532 across the 35 of their papers we have counts for
5 papers · 1 filter
Bayesian Geoadditive Expectile Regression
Elisabeth Waldmann, Fabian Sobotka, Thomas Kneib
Regression classes modeling more than the mean of the response have found a lot of attention in the last years. Expectile regression is a special and computationally convenient cas…
Maximum penalized likelihood estimation in semiparametric capture-recapture models
Théo Michelot, Roland Langrock, Thomas Kneib +1
We discuss the semiparametric modeling of mark-recapture-recovery data where the temporal and/or individual variation of model parameters is explained via covariates. Typically, in…
Nonparametric inference in hidden Markov models using P-splines
Roland Langrock, Thomas Kneib, Alexander Sohn +1
Hidden Markov models (HMMs) are flexible time series models in which the distributions of the observations depend on unobserved serially correlated states. The state-dependent dist…
Semiparametric stochastic volatility modelling using penalized splines
Roland Langrock, Théo Michelot, Alexander Sohn +1
Stochastic volatility (SV) models mimic many of the stylized facts attributed to time series of asset returns, while maintaining conceptual simplicity. The commonly made assumption…
Penalized Likelihood and Bayesian Function Selection in Regression Models
Fabian Scheipl, Thomas Kneib, Ludwig Fahrmeir
Challenging research in various fields has driven a wide range of methodological advances in variable selection for regression models with high-dimensional predictors. In compariso…