gradSEmat: Gradient of the squared exponential kernel, matrix version
In rudazhang/gpc: Gaussian Process Covariance / PCA / SVD Prediction via Separable Transformation
Description
Usage
Arguments
Value
Description
Gradient of the squared exponential kernel, matrix version
Usage
1
Arguments
x
Vector of scalar parameters, or matrix of vector parameters.
len
Length-scale of correlation, isotropic (scalar) or separable (vector), defaults to 1.
K
Kernel matrix, if already computed
Value
a list of partial derivatives of the correlation matrix w.r.t. each lengthscale.
rudazhang/gpc documentation built on Dec. 22, 2021, 8:12 p.m.
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Description Usage Arguments Value
Description
Gradient of the squared exponential kernel, matrix version
Usage
1 |
Arguments
x |
Vector of scalar parameters, or matrix of vector parameters. |
len |
Length-scale of correlation, isotropic (scalar) or separable (vector), defaults to 1. |
K |
Kernel matrix, if already computed |
Value
a list of partial derivatives of the correlation matrix w.r.t. each lengthscale.
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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