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Gaussian Process regression for Empirical Dynamic Modeling
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README.md

GPEDM

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Overview

The goal of GPEDM is to an accessible package for applying Gaussian Process regression for Empirical Dynamic Modeling. The models are mainly intended to modeling time series, and using Gaussian Processes to perform the tricky step of inferring a reasonable model of the underlying dynamics given the observed data.

Installation

You can install GPEDM from GitHub with:

# install.packages("remotes")
remotes::install_github("ha0ye/GPEDM")

If you are on Windows, you may need to install Rtools first, so that you have access to a C++ compiler.

Example

library(GPEDM)
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