Description Usage Arguments Value
View source: R/constraintsReg.R
Fit a linearly constrained regression model with group lasso regularization.
1 2 3 4 5 6 7 | cglasso(y, Z, Zc = NULL, k, W = rep(1, times = p), intercept = TRUE,
A = kronecker(matrix(1, ncol = p), diag(k)), b = rep(0, times = k),
u = 1, mu_ratio = 1.01,
lam = NULL, nlam = 100,lambda.factor = ifelse(n < p1, 0.05, 0.001),
dfmax = p, pfmax = min(dfmax * 1.5, p), tol = 1e-8,
outer_maxiter = 1e+6, outer_eps = 1e-8,
inner_maxiter = 1e+4, inner_eps = 1e-8)
|
y |
respones vector with length n. |
Z |
design matrix of dimension n*p1. |
Zc |
design matrix for unpenalized variables. Default value is NULL. |
k |
the group size in Z. The number of groups is p = p1 / k . |
W |
a vector in length p (the total number of groups), or a matrix with dimension
|
intercept |
Boolean, specifying whether to include an intercept. Default is TRUE. |
A, b |
linear equalities of the form Aβ_{p1} = b, where b is a vector with length k, and A is
a k*p1 matrix.
Default values: b is a vector of 0's and
|
u |
the inital value of the penalty parameter of the augmented Lagrange method adopted in the outer loop. Default value is 1. |
mu_ratio |
the increasing ratio of the penalty parameter |
lam |
a user supplied lambda sequence.
If |
nlam |
the length of the |
lambda.factor |
the factor for getting the minimal lambda in |
dfmax |
limit the maximum number of groups in the model. Useful for handling very large p, if a partial path is desired. Default is p. |
pfmax |
limit the maximum number of groups ever to be nonzero. For example once a group enters the model along the path,
no matter how many times it re-enters the model through the path, it will be counted only once.
Default is |
tol |
tolerance for coefficient to be considered as non-zero. Once the convergence criterion is satisfied, for each element β_j in coefficient vector β, β_j = 0 if β_j < tol. |
outer_maxiter, outer_eps |
|
inner_maxiter, inner_eps |
|
A list of
beta |
a matrix of coefficients. |
lam |
the sequence of lambda values. |
df |
a vector, the number of nonzero groups in estimated coefficients for |
npass |
total number of iteration. |
error |
a vector of error flag. |
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