BIC_lasso: BIC Lasso
In submission-user/cmlDIFlasso: DIF-detection with Lasso-methods in a cML-Framework
Description
Usage
Arguments
Value
Description
Calculates the BIC for an L1 penalized model. Needed for picking a
hyper parameter lambda.
Usage
1
BIC_lasso(Y, betas, deltas, covariates, DIF_type, delta_unres, tolerance)
Arguments
Y
data
betas
vecotr of intercepts
deltas
(ncov x nitems) matrix of DIF-parameters
covariates
(n x ncovs) matrix of covariate values
DIF_type
can be "items", "variables", "all.interactions", "none"
delta_unres
DIF-parameter estimates from unrestricted estimation
tolerance
Value under which parameters are considered equal
to zero for the calculation of degreees of freedom
Value
Returns the BIC for an estimated DIF model with (or without) penalization term
submission-user/cmlDIFlasso documentation built on Dec. 23, 2021, 6:40 a.m.
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Description Usage Arguments Value
Description
Calculates the BIC for an L1 penalized model. Needed for picking a hyper parameter lambda.
Usage
1 | BIC_lasso(Y, betas, deltas, covariates, DIF_type, delta_unres, tolerance)
|
Arguments
Y |
data |
betas |
vecotr of intercepts |
deltas |
(ncov x nitems) matrix of DIF-parameters |
covariates |
(n x ncovs) matrix of covariate values |
DIF_type |
can be "items", "variables", "all.interactions", "none" |
delta_unres |
DIF-parameter estimates from unrestricted estimation |
tolerance |
Value under which parameters are considered equal to zero for the calculation of degreees of freedom |
Value
Returns the BIC for an estimated DIF model with (or without) penalization term
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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