simdata

simdata0

<p><code>simdata</code> is a simple test data set simulated from two clusters and consisting of 100 curves, with 50 curves belonging to one cluster and 50 to another. The test data set is a copy of the <code>simdata</code> of James and Sugar (2003).</p>

Routines for model-based functional cluster analysis for functional data with optional covariates. The idea is to cluster functional subjects (often called functional objects) into homogenous groups by using spline smoothers (for functional data) together with scalar covariates. The spline coefficients and the covariates are modelled as a multivariate Gaussian mixture model, where the number of mixtures corresponds to the number of clusters. The parameters of the model are estimated by maximizing the observed mixture likelihood via an EM algorithm (Arnqvist and Sjöstedt de Luna, 2019) <doi:10.48550/arXiv.1904.10265>. The clustering method is used to analyze annual lake sediment from lake Kassjön (Northern Sweden) which cover more than 6400 years and can be seen as historical records of weather and climate.

Natalya Pya

fdaMocca

Model-Based Clustering for Functional Data with Covariates

Per Arnqvist

Sara Sjöstedt de Luna

simdata function

<p><code>simdata</code> is a list of three vectors called as <code>x</code>, <code>curve</code> and <code>time</code>. 
<code>simdata0</code> is a reduced dataset with only six curves in each cluster.</p>

simdata: Simulated data

Description

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References