This class contains all the input parameters to run CLERE.
[numeric]: The vector of observed responses - size
[matrix]: The matrix of predictors - size
n rows and
[numeric]: A non-negative penalty term that controls simultaneouly clusetering and sparsity.
[numeric]: A vector of initial guess of the model parameters. The authors suggest to use coefficients obtained after fitting a ridge regression with the shrinkage parameter selected using AIC criterion.
[numeric]: A tolerance threshold that control the convergence of the algroithm. The default value fixed in Bondell's initial script is 1e-5.
[integer]: Maximum number of iterations in the algorithm.
[numeric]: Fitted intercept.
[integer]: Model dimensionality.
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