rgasp-class | R Documentation |
S4 class for Robust GaSP if the range and noise-variance ratio parameters are given and/or have been estimated.
Objects of this class are created and initialized with the function rgasp
that computes the calculations needed for setting up the analysis.
p
:Object of class integer
. The dimensions of the inputs.
num_obs
:Object of class integer
. The number of observations.
input
:Object of class matrix
with dimension n x p. The design of experiments.
output
:Object of class matrix
with dimension n x 1. The Observations or output vector.
X
:Object of class matrix
of with dimension n x q. The mean basis function, i.e. the trend function.
zero_mean
:A character
to specify whether the mean is zero or not. "Yes" means it has zero mean and "No"" means the mean is not zero.
q
:Object of class integer
. The number of mean basis.
LB
:Object of class vector
with dimension p x 1. The lower bound for inverse range parameters beta.
beta_initial
:Object of class vector
with the initial values of inverse range parameters p x 1.
beta_hat
:Object of class vector
with dimension p x 1. The inverse-range parameters.
log_post
:Object of class numeric
with the logarithm of marginal posterior.
R0
:Object of class list
of matrices where the j-th matrix is an absolute difference matrix of the j-th input vector.
theta_hat
:Object of class vector
with dimension q x 1. The the mean (trend) parameter.
L
:Object of class matrix
with dimension n x n. The Cholesky decomposition of the correlation matrix R
, i.e.
L\%*\%t(L)=R
sigma2_hat
:Object of the class numeric
. The estimated variance parameter.
LX
:Object of the class matrix
with dimension q x q. The Cholesky decomposition of the correlation matrix
t(X)\%*\%R^{-1}\%*\%X
CL
:Object of the class vector
used for the lower bound and the prior.
nugget
:A numeric
object used for the noise-variance ratio parameter.
nugget.est
:A logical
object of whether the nugget is estimated (T) or fixed (F).
kernel_type
:A vector
of character
to specify the type of kernel to use.
alpha
:Object of class vector
with dimension p x 1 for the roughness parameters in the kernel.
method
:Object of class character
to specify the method of parameter estimation. There are three values: post_mode
, mle
and mmle
.
isotropic
:Object of class logical
to specify whether the kernel is isotropic.
call
:The call
to rgasp
function to create the object.
Prints the main slots of the object.
See predict
.
The response output
must have one dimension.
The number of observations in input
must be equal to the number of experiments output
.
Mengyang Gu [aut, cre], Jesus Palomo [aut], James Berger [aut]
Maintainer: Mengyang Gu <mengyang@pstat.ucsb.edu>
RobustGaSP
for more details about how to create a RobustGaSP
object.
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