create.lineqGP: Creation Method for the '"lineqGP"' S3 Class

In lineqGPR: Gaussian Process Regression Models with Linear Inequality Constraints

Description

Creation method for the "lineqGP" S3 class.

Usage

## S3 method for class 'lineqGP'
create(x, y, constrType)

Arguments

x	a vector or matrix with the input data. The dimensions should be indexed by columns.
y	a vector with the output data.
constrType	a character string corresponding to the type of the inequality constraint. Options: "boundedness", "monotonicity", "convexity", "linear"; Multiple constraints can be also defined, e.g. constrType = c("boundedness", "monotonicity").

Value

A list with the following elements.

x,y,constrType	see Arguments.
d	a number corresponding to the input dimension.
constrIdx	for d > 1, a logical vector with the indices of active constrained dimensions.
localParam	a list with specific parameters required for "lineqGP" models: m (number of basis functions), sampler, and samplingParams. See simulate.lineqGP.
kernParam	a list with the kernel parameters: par (kernel parameters), type, nugget. See kernCompute
bounds	the limit values if constrType = "boundedness".
(Lambda,lb,ub)	the linear system of inequalities if constrType = "linear".

Author(s)

A. F. Lopez-Lopera.

References

Lopez-Lopera, A. F., Bachoc, F., Durrande, N., and Roustant, O. (2017), "Finite-dimensional Gaussian approximation with linear inequality constraints". ArXiv e-prints [link]

See Also

augment.lineqGP, predict.lineqGP, simulate.lineqGP

Examples

# creating the model
sigfun <- function(x) return(1/(1+exp(-7*(x-0.5))))
x <- seq(0, 1, length = 5)
y <- sigfun(x)
model <- create(class = "lineqGP", x, y, constrType = "monotonicity")
model

lineqGPR documentation built on Jan. 11, 2020, 9:23 a.m.