inv_pd: Compute the inverse of a positive-definite matrix
In lgaborini/bayessource: Bayesian approach to evaluate whether two datasets come from the same population
Description
Usage
Arguments
Value
See Also
View source: R/elicit_priors.R
Description
Compute the inverse of a positive-definite matrix using Cholesky decomposition.
Usage
1
inv_pd(X)
Arguments
X
a positive-definite matrix
Value
the inverse of X
See Also
Other math functions:
chol2inv(),
inv_Cholesky_from_Cholesky(),
inv_sympd_tol(),
inv_triangular(),
ldet_from_Cholesky(),
logCummeanExp(),
logCumsumExp(),
logSumExpMean(),
logSumExp()
lgaborini/bayessource documentation built on Nov. 9, 2021, 2:10 p.m.
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Description Usage Arguments Value See Also
View source: R/elicit_priors.R
Description
Compute the inverse of a positive-definite matrix using Cholesky decomposition.
Usage
1 | inv_pd(X)
|
Arguments
X |
a positive-definite matrix |
Value
the inverse of X
See Also
Other math functions:
chol2inv(),
inv_Cholesky_from_Cholesky(),
inv_sympd_tol(),
inv_triangular(),
ldet_from_Cholesky(),
logCummeanExp(),
logCumsumExp(),
logSumExpMean(),
logSumExp()
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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