grouplasso2pop_linreg_grid: Fit grouplasso2pop regression estimator over a grid of lambda...

In gregorkb/semipadd2pop: Combine two data sets to fit semiparametric additive models

Fit grouplasso2pop regression estimator over a grid of lambda and eta values

Description

Fit grouplasso2pop regression estimator over a grid of lambda and eta values

Usage

grouplasso2pop_linreg_grid(
  Y1,
  X1,
  groups1,
  Y2,
  X2,
  groups2,
  rho1,
  rho2,
  n.lambda,
  n.eta,
  lambda.min.ratio,
  lambda.max.ratio = 1,
  eta.min.ratio = 0.001,
  eta.max.ratio = 10,
  w1,
  w2,
  w,
  AA1,
  AA2,
  Com,
  tol = 1e-04,
  maxiter = 500,
  report.prog = FALSE
)

Arguments

Y1	the continuous response vector of data set 1
X1	matrix containing the design matrices for data set 1
groups1	a vector indicating to which group each covariate of data set 1 belongs
Y2	the continuous response vector of data set 2
X2	matrix containing the design matrices for data set 2
groups2	a vector indicating to which group each covariate of data set 2 belongs
rho1	weight placed on the first data set
rho2	weight placed on the second data set
n.lambda	the number of lambda values desired
n.eta	the number of eta values desired
lambda.min.ratio	ratio of the smallest lambda value to the smallest value of lambda which admits no variables to the model
lambda.max.ratio	ratio of the largest lambda value to the smallest value of lambda which admits no variables to the model
eta.min.ratio	ratio of the smallest to largest value in the sequence of eta values
eta.max.ratio	controls the largest value of eta in the eta sequence
w1	group-specific weights for different penalization across groups in data set 1
w2	group-specific weights for different penalization across groups in data set 2
w	group-specific weights for different penalization toward similarity for different groups
AA1	a list of the matrices A2j
Com	the indices of the covariate groups which are common in the two datasets
tol	a convergence criterion
maxiter	the maximum allowed number of iterations
report.prog	a logical indicating whether the progress of the algorithm should be printed to the console

Value

a list containing the fits over a grid of lambda and eta values as well as the vector of lambda values and the vector of eta values

Examples

data <- get_grouplasso2pop_data(n1 = 400, n2 = 600, response = "continuous")

grouplasso2pop_lingreg_grid.out <- grouplasso2pop_linreg_grid(Y1 = data$Y1,
                                                              X1 = data$X1,
                                                              groups1 = data$groups1,
                                                              Y2 = data$Y2,
                                                              X2 = data$X2,
                                                              groups2 = data$groups2,
                                                              rho1 = 1,
                                                              rho2 = 2,
                                                              n.lambda = 10,
                                                              n.eta = 5,
                                                              lambda.min.ratio = 0.001,
                                                              lambda.max.ratio = .5,
                                                              w1 = data$w1,
                                                              w2 = data$w2,
                                                              w = data$w,
                                                              AA1 = data$AA1,
                                                              AA2 = data$AA2,
                                                              Com = data$Com,
                                                              tol = 1e-3,
                                                              maxiter = 500,
                                                              report.prog = TRUE)

gregorkb/semipadd2pop documentation built on Oct. 2, 2022, 1:37 p.m.