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Bayesian Non-Parametric Dependent Models for Time-Indexed Functional Data
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | growfunctions |
Bayesian Non-Parametric Dependent Models for Time-Indexed Functional Data |
Statements
12 December 2023
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Estimates a collection of time-indexed functions under either of Gaussian process (GP) or intrinsic Gaussian Markov random field (iGMRF) prior formulations where a Dirichlet process mixture allows sub-groupings of the functions to share the same covariance or precision parameters. The GP and iGMRF formulations both support any number of additive covariance or precision terms, respectively, expressing either or both of multiple trend and seasonality.
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