loadest_gp

class loadest_gp.LoadestGPMarginalGPyTorch(model_config: ModelConfig = ModelConfig(transform='log'))

Gaussian Process implementation of the LOAD ESTimation (LOADEST) model

This model currrently uses the marginal likelihood implementation, which is fast but does not account for censored data. Censored data require a slower latent variable implementation.

build_model(X, y) → ExactGP

Build marginal likelihood version of LoadestGP

class loadest_gp.LoadestGPMarginalPyMC(model_config: ModelConfig = ModelConfig(transform='log'))

Gaussian Process implementation of the LOAD ESTimation (LOADEST) model

This model currrently uses the marginal likelihood implementation, which is fast but does not account for censored data. Censored data require a slower latent variable implementation.

build_model(X, y) → Model

Build marginal likelihood version of LoadestGP

Modules

models
plot	Plotting functions
providers
utils