penalized_regression_parameters.RegressHaplo: Returns the matrices and vectors associated with the...
In SLeviyang/RegressHaplo: Haplotype Reconstruction Using Penalized Regression
View source: R/RegressHaplo_util.R
penalized_regression_parameters.RegressHaplo R Documentation
Returns the matrices and vectors associated with the regression
optimization
Description
Returns the matrices and vectors associated with the regression
optimization
Usage
penalized_regression_parameters.RegressHaplo(df, h, position_fit = F)
Arguments
df
read table
h
haplotype matrix
Details
The regression solves
min |y - P*pi|^2 + rho pi^T*M*pi
subject to: sum pi_i = 1, pi_i ge 0.
Value
the matrix P and the vector y as a list. M is implicit
and so not computed.
SLeviyang/RegressHaplo documentation built on June 1, 2022, 10:48 p.m.
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View source: R/RegressHaplo_util.R
| penalized_regression_parameters.RegressHaplo | R Documentation |
Returns the matrices and vectors associated with the regression optimization
Description
Returns the matrices and vectors associated with the regression optimization
Usage
penalized_regression_parameters.RegressHaplo(df, h, position_fit = F)
Arguments
df |
read table |
h |
haplotype matrix |
Details
The regression solves min |y - P*pi|^2 + rho pi^T*M*pi subject to: sum pi_i = 1, pi_i ge 0.
Value
the matrix P and the vector y as a list. M is implicit and so not computed.
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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