GauPro_Gauss_LOO: Corr Gauss GP using inherited optim

In GauPro: Gaussian Process Fitting

Corr Gauss GP using inherited optim

Description

Corr Gauss GP using inherited optim

Corr Gauss GP using inherited optim

Format

R6Class object.

Value

Object of R6Class with methods for fitting GP model.

Super classes

GauPro::GauPro -> GauPro::GauPro_Gauss -> GauPro_Gauss_LOO

Public fields

use_LOO

Should the leave-one-out correction be used?

tmod

Second GP model fit to the t-values of leave-one-out predictions

Methods

Public methods

• GauPro_Gauss_LOO$update()

• GauPro_Gauss_LOO$pred_one_matrix()

• GauPro_Gauss_LOO$print()

• GauPro_Gauss_LOO$clone()

Inherited methods

• GauPro::GauPro$cool1Dplot()
• GauPro::GauPro$deviance_searchnug()
• GauPro::GauPro$fit()
• GauPro::GauPro$grad_norm()
• GauPro::GauPro$initialize_GauPr()
• GauPro::GauPro$loglikelihood()
• GauPro::GauPro$nugget_update()
• GauPro::GauPro$optim()
• GauPro::GauPro$optimRestart()
• GauPro::GauPro$plot()
• GauPro::GauPro$plot1D()
• GauPro::GauPro$plot2D()
• GauPro::GauPro$pred()
• GauPro::GauPro$pred_LOO()
• GauPro::GauPro$pred_mean()
• GauPro::GauPro$pred_meanC()
• GauPro::GauPro$pred_var()
• GauPro::GauPro$predict()
• GauPro::GauPro$sample()
• GauPro::GauPro$update_K_and_estimates()
• GauPro::GauPro$update_corrparams()
• GauPro::GauPro$update_data()
• GauPro::GauPro$update_nugget()
• GauPro::GauPro_Gauss$corr_func()
• GauPro::GauPro_Gauss$deviance()
• GauPro::GauPro_Gauss$deviance_fngr()
• GauPro::GauPro_Gauss$deviance_grad()
• GauPro::GauPro_Gauss$deviance_log()
• GauPro::GauPro_Gauss$deviance_log2()
• GauPro::GauPro_Gauss$deviance_log2_fngr()
• GauPro::GauPro_Gauss$deviance_log2_grad()
• GauPro::GauPro_Gauss$deviance_log_grad()
• GauPro::GauPro_Gauss$deviance_theta()
• GauPro::GauPro_Gauss$deviance_theta_log()
• GauPro::GauPro_Gauss$get_optim_functions()
• GauPro::GauPro_Gauss$grad()
• GauPro::GauPro_Gauss$grad_dist()
• GauPro::GauPro_Gauss$hessian()
• GauPro::GauPro_Gauss$initialize()
• GauPro::GauPro_Gauss$param_optim_jitter()
• GauPro::GauPro_Gauss$param_optim_lower()
• GauPro::GauPro_Gauss$param_optim_start()
• GauPro::GauPro_Gauss$param_optim_start0()
• GauPro::GauPro_Gauss$param_optim_upper()
• GauPro::GauPro_Gauss$update_params()

---

Method update()

Update the model, can be data and parameters

Usage

GauPro_Gauss_LOO$update(
  Xnew = NULL,
  Znew = NULL,
  Xall = NULL,
  Zall = NULL,
  restarts = 5,
  param_update = self$param.est,
  nug.update = self$nug.est,
  no_update = FALSE
)

Arguments

Xnew

New X matrix

Znew

New Z values

Xall

Matrix with all X values

Zall

All Z values

restarts

Number of optimization restarts

param_update

Should the parameters be updated?

nug.update

Should the nugget be updated?

no_update

Should none of the parameters/nugget be updated?

---

Method pred_one_matrix()

Predict mean and se for given matrix

Usage

GauPro_Gauss_LOO$pred_one_matrix(XX, se.fit = F, covmat = F)

Arguments

XX

Points to predict at

se.fit

Should the se be returned?

covmat

Should the covariance matrix be returned?

---

Method print()

Print this object

Usage

GauPro_Gauss_LOO$print()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

GauPro_Gauss_LOO$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

n <- 12
x <- matrix(seq(0,1,length.out = n), ncol=1)
y <- sin(2*pi*x) + rnorm(n,0,1e-1)
gp <- GauPro_Gauss_LOO$new(X=x, Z=y, parallel=FALSE)

GauPro documentation built on April 11, 2023, 6:06 p.m.