as.S3prediction: Convert a 'rgasp' or 'ppgasp' 'S4 object' prediction into a...

In RobustGaSP: Robust Gaussian Stochastic Process Emulation

Convert a rgasp or ppgasp S4 object prediction into a S3 object

Description

This function converts the default S4 object prediction into a S3 object

Usage

as.S3prediction(object, ...)

Arguments

object	an object of class predrgasp-class or ppgasp-class is converted into a S3 object
...	Extra arguments to be passed to the function (not implemented yet).

Value

The returned value is a list with

mean	predictive mean for the testing inputs.
lower95	lower bound of the 95% posterior credible interval.
upper95	upper bound of the 95% posterior credible interval.
sd	standard deviation of each testing_input.

Author(s)

Mengyang Gu [aut, cre], Jesus Palomo [aut], James Berger [aut]

Maintainer: Mengyang Gu <[e-mail]>

Examples

  #------------------------
  # a 3 dimensional example
  #------------------------
  # dimensional of the inputs
  dim_inputs <- 3    
  # number of the inputs
  num_obs <- 30       
  # uniform samples of design
  input <- matrix(runif(num_obs*dim_inputs), num_obs,dim_inputs) 
  
  # Following codes use maximin Latin Hypercube Design, which is typically better than uniform
  # library(lhs)
  # input <- maximinLHS(n=num_obs, k=dim_inputs)  ##maximin lhd sample
  
  # outputs from the 3 dim dettepepel.3.data function
  
  output = matrix(0,num_obs,1)
  for(i in 1:num_obs){
    output[i]<-dettepepel.3.data (input[i,])
  }
  
  # use constant mean basis, with no constraint on optimization
  m1<- rgasp(design = input, response = output, lower_bound=FALSE)
  
  # the following use constraints on optimization
  # m1<- rgasp(design = input, response = output, lower_bound=TRUE)
  
  # the following use a single start on optimization
  # m1<- rgasp(design = input, response = output, lower_bound=FALSE, multiple_starts=FALSE)
  
  # number of points to be predicted 
  num_testing_input <- 5000    
  # generate points to be predicted
  testing_input <- matrix(runif(num_testing_input*dim_inputs),num_testing_input,dim_inputs)
  # Perform prediction
  m1.predict<-predict(m1, testing_input, outasS3 = FALSE)
  
  # The returned object is of predrgasp-class
  str(m1.predict)
  # To have the prediction as a list
  m1.predict.aslist <- as.S3prediction(m1.predict)
  str(m1.predict.aslist)
  

RobustGaSP documentation built on June 1, 2022, 9:08 a.m.