Model based functional clustering of varved lake sediments

Abstract

In this paper we propose a model-based method for clustering subjects for which functional data together with covariates are observed. The model allows the covariance structures within the different clusters to be different. The model thus extends a model proposed by James and Sugar (2003). We derive an EM algorithm to estimate the parameters. The method is applied to annually laminated (varved) sediment from lake Kassj\"on in northern Sweden, to infer on past climate changes.