Beitrag in einem Sammelband

Exploratory exponential tilting

Camarda, C. G., Eilers, P. H. C., Gampe, J.
In: Muggeo, V. M. R., Capursi, V., Boscaino, G., Lovison, G. (Eds.): Proceedings of the 28th International Workshop on Statistical Modelling, Palermo 8-12 July, 2013: volume 1, part II, 97–102
Palermo, Università di Palermo, Dipartimento di Scienze Statistiche e Matematiche (2013)


We propose a new technique to summarize several distributions parsimoniously by employing ideas from Exponential Tilting (ET). We assume that the observed data are generated by densities that can be derived from a single (latent) reference distribution by ET, i.e., while preserving the sample means they have minimal Kullback-Leibler distance to the reference distribution. We show how the reference densitiy and the resulting Lagrange multipliers can be estimated by penalized likelihood in a GLM setting. We also suggest an extension of the model, if simple ET does not lead to a satisfactory summary. We illustrate the methodology by two applications.
Das Max-Planck-Institut für demografische Forschung (MPIDR) in Rostock ist eines der international führenden Zentren für Bevölkerungswissenschaft. Es gehört zur Max-Planck-Gesellschaft, einer der weltweit renommiertesten Forschungsgemeinschaften.