Examples
¶
1D kernel basics
Initialise the GPtide object and sample from the prior
Make a prediction at new points
Make a prediction of the full conditional distribution at new points
1D parameter estimation using maximum likelihood estimation
Generate some data
Inference
1D parameter estimation using MCMC
Generate some data
Inference
Find sample with highest log prob
Posterior density plot
Posterior corner plot
Condition and make predictions
1D parameter estimation using MCMC: kernel multplication
Generate some data
Inference
Find sample with highest log prob
Posterior density plot
Posterior corner plot
Condition and make predictions
2D parameter estimation using MCMC
Generate some data
Inference
Find sample with highest log prob
Posterior density plot
Posterior corner plot
Condition and make predictions
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gptide: a lightweight module for Gaussian Process regression
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