Description Usage Arguments Value Examples
Generate the proximal operator for the requested penalty
1 2 3 | initializeOperator(lambda1, index.penalty1, index.model1, lambda2,
index.penalty2, index.model2, lambdaG, index.penaltyG, index.modelG, lambdaN,
index.penaltyN, nrow, ncol, equivariance, constrain.variance, index.variance)
|
lambda1 |
lasso penalization parameter. |
index.penalty1 |
a list containing the position of lasso penalized parameters in the vector of parameters. |
index.model1 |
the index of the model relative to each lasso penalized parameter |
lambda2 |
ridge penalization parameter. |
index.penalty2 |
a list containing the position of ridge penalized parameters in the vector of parameters. |
index.model2 |
the index of the model relative to each ridge penalized parameter |
lambdaG |
group lasso penalization parameter. |
index.penaltyG |
a list containing the position of group lasso parameters in the vector of parameters. |
index.modelG |
the index of the model relative to each group lasso penalized parameter |
lambdaN |
nuclear norm penalization parameter. |
index.penaltyN |
a list containing the position of the parameters corresponding to each image in the vector of parameters. |
nrow |
a vector containing the number of rows of each image. |
ncol |
a vector containing the number of columnss of each image. |
equivariance |
should the lambda parameter be multiplied with the first variance parameter? |
constrain.variance |
should the variance parameters be exponential trans |
index.variance |
the position of the variance parameters in coef |
a list containing the proximal operator and the penalty funtion
1 | lavaPenalty:::initializeOperator(lasso = TRUE, ridge = FALSE, groupLasso = FALSE, nuclearNorm = FALSE)
|
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