compute.covariance.from.distance: Compute unscaled covariance matrix from a supplied distance...
In peterrobertcurtis/SSM: Fit and Analyze Smooth Supersaturated Models
Description
This is a legacy function and is not used.
Usage
1
compute.covariance.from.distance(distance, r, type = "exp", ssm)
Arguments
distance
A matrix. A symmetric matrix of distances between design
points.
r
A number. The length parameter for the correlation function
type
(optional) Character. Specifies the correlation function. Default
behaviour is to use "exp" for a squared exponential correlation.
"Matern32" uses a Matern 3/2 correlation.
ssm
(obsolete) An SSM object. Used for the removed
"ssm" correlation function which tried to use the local smoothness
of the SSM to measure distances.
peterrobertcurtis/SSM documentation built on May 25, 2019, 2:10 a.m.
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Description
This is a legacy function and is not used.
Usage
1 | compute.covariance.from.distance(distance, r, type = "exp", ssm)
|
Arguments
distance |
A matrix. A symmetric matrix of distances between design points. |
r |
A number. The length parameter for the correlation function |
type |
(optional) Character. Specifies the correlation function. Default
behaviour is to use |
ssm |
(obsolete) An SSM object. Used for the removed
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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