lmSolve: Minimum Norm Regresion with Moore-Penrose Inverse
In abnormally-distributed/Bayezilla: Bayesian Models With JAGS and Several Utilities for Data Exploration and Model Evaluation.
Description
Usage
Arguments
Value
Examples
Description
A fast solver for simple least squares models. Returns coefficients only.
Solves with moore-penrose pseudoinversion which is very fast and tolerant
to non-positive definite model matrices.
Usage
1
Arguments
formula
formula
data
data frame
w
optional weights
tolerance
tolerance
Value
a vector
Examples
1
lmSolve()
abnormally-distributed/Bayezilla documentation built on Oct. 31, 2019, 1:57 a.m.
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Description Usage Arguments Value Examples
Description
A fast solver for simple least squares models. Returns coefficients only. Solves with moore-penrose pseudoinversion which is very fast and tolerant to non-positive definite model matrices.
Usage
1 |
Arguments
formula |
formula |
data |
data frame |
w |
optional weights |
tolerance |
tolerance |
Value
a vector
Examples
1 | lmSolve()
|
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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