Sums of smooth exponentials to decompose complex series of counts

CG Camarda, Paul Eilers, J Gampe

Research output: Contribution to journalArticleAcademicpeer-review

14 Citations (Scopus)

Abstract

Representing the conditional mean in Poisson regression directly as a sum of smooth components can provide a realistic model of the data generating process. Here, we present an approach that allows such an additive decomposition of the expected values of counts. The model can be formulated as a penalized composite link model and can, therefore, be estimated by a modified iteratively weighted least-squares algorithm. Further shape constraints on the smooth additive components can be enforced by additional penalties, and the model is extended to two dimensions. We present two applications that motivate the model and demonstrate the versatility of the approach.
Original languageUndefined/Unknown
Pages (from-to)279-296
Number of pages18
JournalStatistical Modelling
Volume16
Issue number4
DOIs
Publication statusPublished - 2016

Research programs

  • EMC NIHES-01-66-01

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