nugget: Gaussian Process Nugget Related Functions

Description Usage Arguments Value Note Author(s) References Examples

Description

Functions for detecting replicates and for calculating sample variance at specific design points

Usage

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Arguments

X

the design matrix

Y

a vector (or 1 column matrix) of observations

Value

varPerReps returns a 1-column matrix where element i corresponds to the sample variance in observations corresponding to design point X[i]

estimateNugget returns a double calculated by taking the mean of the matrix returned by varPerReps

anyReps returns TRUE if two or more rows of X are identical

Note

These functions are used by mlegp to set an initial value of the nugget when a constant nugget is being estimated. The function varPerReps may also be useful for specifying the form of the nugget matrix for use with mlegp.

Author(s)

Garrett M. Dancik dancikg@easternct.edu

References

https://github.com/gdancik/mlegp/

Examples

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x = matrix(c(1,1,2,3,3))   # the design matrix
y = matrix(c(5,6,7,0,10))  # output

anyReps(x)
varPerReps(x,y)
estimateNugget(x,y)

mlegp documentation built on Oct. 23, 2020, 5:53 p.m.