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User Guide
Getting started
Installation
Prerequisites
Stable Version
Development Version
Testing
Examples
Upgrading from pre-1.0 versions
Kernels
Common parameters
Implementation details & modeling interface
Stationary kernels
Non-stationary kernels
Combining kernels
Implementing new kernels
The GP object
Solvers
Basic Solver
HODLR Solver
Modeling protocol
The protocol
A simple example
Tutorials
A gentle introduction to Gaussian Process Regression
Model fitting with correlated noise
A Simple Mean Model
Simulated Dataset
Assuming White Noise
Modeling the Noise
The Final Fit
Hyperparameter optimization
Optimization
Sampling & Marginalization
Scaling Gaussian Processes to big datasets
Implementing new kernels
The kernel function
Kernel specification
George
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Upgrading from pre-1.0 versions
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Upgrading from pre-1.0 versions
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