construct.K: Construct the K matrix for a given multivariate basis.
In peterrobertcurtis/SSM: Fit and Analyze Smooth Supersaturated Models
Description
Usage
Arguments
Value
Description
This function constructs the K matrix for a given multivariate basis assuming
the basis is a Legendre polynomial basis and the smoothing criterion is the
Frobenius norm of the Hessian integrated over [-1, 1]^d.
Usage
1
construct.K(basis)
Arguments
basis
A matrix. Rows of the matrix are taken as the exponent vectors
of the leading terms of a Legendre polynomial basis.
Value
A matrix where each entry is <f, g> with
<f, g> = \int_X
∑_{i,j}\frac{d^2f}{dx_idx_j}\frac{d^2g}{dx_idx_j} dx,
with f, g
being the Legendre polynomials described by the appropriate exponent vectors.
peterrobertcurtis/SSM documentation built on May 25, 2019, 2:10 a.m.
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Description Usage Arguments Value
Description
This function constructs the K matrix for a given multivariate basis assuming the basis is a Legendre polynomial basis and the smoothing criterion is the Frobenius norm of the Hessian integrated over [-1, 1]^d.
Usage
1 | construct.K(basis)
|
Arguments
basis |
A matrix. Rows of the matrix are taken as the exponent vectors of the leading terms of a Legendre polynomial basis. |
Value
A matrix where each entry is <f, g> with
<f, g> = \int_X ∑_{i,j}\frac{d^2f}{dx_idx_j}\frac{d^2g}{dx_idx_j} dx,
with f, g being the Legendre polynomials described by the appropriate exponent vectors.
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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