kernel_cov: Calculate a kernel covariance matrix.
In markdrisser/convoSPAT: Convolution-Based Nonstationary Spatial Modeling
Description
Usage
Arguments
Value
Examples
View source: R/convoSPAT_simulate.R
Description
kernel_cov calculates a 2 x 2 matrix based on the eigendecomposition
components (two eigenvalues and angle of rotation).
Usage
1
kernel_cov(params)
Arguments
params
A vector of three parameters, corresponding to
(lam1, lam2, eta). The eigenvalues (lam1 and lam2) must be positive.
Value
A 2 x 2 kernel covariance matrix.
Examples
1
kernel_cov(c(1, 2, pi/3))
markdrisser/convoSPAT documentation built on May 21, 2019, 11:48 a.m.
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Description Usage Arguments Value Examples
View source: R/convoSPAT_simulate.R
Description
kernel_cov calculates a 2 x 2 matrix based on the eigendecomposition
components (two eigenvalues and angle of rotation).
Usage
1 | kernel_cov(params)
|
Arguments
params |
A vector of three parameters, corresponding to (lam1, lam2, eta). The eigenvalues (lam1 and lam2) must be positive. |
Value
A 2 x 2 kernel covariance matrix.
Examples
1 | kernel_cov(c(1, 2, pi/3))
|
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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