hetGPy

Examples:

  • hetGPy Example Notebooks
    • hetGPy Intro: Background and Basic Usage
      • What is hetGPy?
      • Why is a Python port needed when we have rpy2 to call R code from Python?
      • Basic Setup
      • Noiseless case
      • Fast Estimation under Replication
      • Heteroskedastic Gaussian Process Regression
      • Specifying initializations for the hyperparamters
      • Specifying known values of hyperparameters
    • hetGPy Introduction and Example
      • Setup
    • hetGPy SIR Example
      • The SIR Simulation Model
    • Integrated Mean Squared Prediction Error
    • hetGPy Sequential Learning
    • Sequential Design
      • Sequential Design for Expected Improvement
      • Sequential Design for Integrated Mean-Squared Prediction Error
    • Common Random Number GP

Reference:

  • API
    • hetGP
      • hetGP
        • hetGP.LOO_preds_nugs()
        • hetGP.copy()
        • hetGP.dlogLikHet()
        • hetGP.logLikHet()
        • hetGP.mleHetGP()
        • hetGP.plot()
        • hetGP.predict()
        • hetGP.rebuild()
        • hetGP.strip()
        • hetGP.summary()
        • hetGP.update()
    • homGP
      • homGP
        • homGP.copy()
        • homGP.dlogLikHom()
        • homGP.get()
        • homGP.logLikHom()
        • homGP.mleHomGP()
        • homGP.plot()
        • homGP.predict()
        • homGP.rebuild()
        • homGP.strip()
        • homGP.summary()
        • homGP.update()
    • contour
      • crit_ICU()
      • crit_MCU()
      • crit_MEE()
      • crit_cSUR()
      • crit_tMSE()
    • covariance_functions
    • optim
    • IMSE
      • IMSPE()
      • Wij()
      • allocate_mult()
      • deriv_crit_IMSPE()
      • horizon()
      • lhs_EP()
      • maximinSA_LHS()
      • mi()
      • phiP()
    • find_reps
    • LOO
    • plot
hetGPy
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