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- W253669852 abstract "This paper uses the interface between two disciplines�phylogenetics and functional dataanalysis�to aid the analysis of rich ancestral data like continuous curves. We place Gaus-sian processes on phylogenies in order to perform evolutionary inference on such functionaldata objects. Unlike morphological summaries, which reduce data dimension, this approachallows one to make inferential statements about curves themselves. We provide a modifiedcovariance function that corrects for the relationships between states at different points ona phylogeny and discuss its use in inference. In general, this covariance is expressed as thesolution of an integral equation and we note that, for a given Gaussian process, a set ofsolutions sufficient for all phylogenies may be precomputed as a library which, for station-ary processes, is one dimensional. This work has relevance for those wanting to performinference on functional data objects related by an evolutionary process; it also specifies aclass of hierarchical clustering algorithms for functional data objects and can be used formultivariate time series forecasting." @default.
- W253669852 created "2016-06-24" @default.
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- W253669852 date "2011-02-18" @default.
- W253669852 modified "2023-09-27" @default.
- W253669852 title "Evolutionary Inference for Functional Data: Using Gaussian Processes on Phylogenies to Study Shape Evolution" @default.
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