cov.independent: Independant covariance function. Is zero everywhere except...
In JimSkinner/spca: Structured PCA
View source: R/covariance-functions.R
Description
Independant covariance function. Is zero everywhere except for inputs with
zero distance. Has single hyperparameter of log signal variance. All nonzero
outputs are equal to the signal variance.
Usage
1
cov.independent(X, X2, beta, D = NA, ...)
Arguments
X
Matrix of data
X2
(optional) second matrix of data; if omitted, X is used.
beta
The single hyperparameter: the log of the signal variance
JimSkinner/spca documentation built on Aug. 19, 2018, 7 a.m.
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View source: R/covariance-functions.R
Description
Independant covariance function. Is zero everywhere except for inputs with zero distance. Has single hyperparameter of log signal variance. All nonzero outputs are equal to the signal variance.
Usage
1 | cov.independent(X, X2, beta, D = NA, ...)
|
Arguments
X |
Matrix of data |
X2 |
(optional) second matrix of data; if omitted, X is used. |
beta |
The single hyperparameter: the log of the signal variance |
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.
As an Amazon Associate I earn from qualifying purchases.
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