Browsing Fakultät für Mathematik und Informatik (inkl. GAUSS) by Referee "Kneib, Thomas Prof. Dr."
Now showing items 1-3 of 3
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Empirical Bayesian Smoothing Splines for Signals with Correlated Errors: Methods and Applications
(2016-08-12)Smoothing splines is a well stablished method in non-parametric statistics, although the selection of the smoothness degree of the regression function is rarely addressed and, instead, a two times differentiable function, ... -
Model choice and variable selection in mixed & semiparametric models
(2015-04-10)Semiparametric and mixed models allow different kinds of data structures and data types to be considered in regression models. Spatial and temporal structures of discrete or spatial data can be treated as flexibly as, ... -
Statistical Inference for Propagation Processes on Complex Networks
(2014-07-29)Scientists of various research fields have discovered the advantages of network-centric analysis, which captures complex systems by networks and allows for their representation as a collection of nodes connected by links. ...