grouplasso_gt: Compute group lasso for two populations with group testing...

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

Compute group lasso for two populations with group testing data

Description

Compute group lasso for two populations with group testing data

Usage

grouplasso_gt(
  Y,
  Z,
  Se,
  Sp,
  E.approx,
  X,
  groups,
  lambda,
  w,
  tol = 0.001,
  maxiter = 1000,
  init = NULL,
  report.prog = FALSE
)

Arguments

Y	Group testing output in the format as output by one of the functions individual.assay.gen, masterpool.assay.gen, dorfman.assay.gen, or array.assay.gen.
Z	Group testing output in the format as output by one of the functions individual.assay.gen, masterpool.assay.gen, dorfman.assay.gen, or array.assay.gen.
Se	A vector of testing sensitivities, where the first element is the testing specificity for pools and the second entry is the test specificity for individual testing, if applicable.
Sp	A vector of testing specificities, where the first element is the testing specificity for pools and the second entry is the test specificity for individual testing, if applicable.
E.approx	a logical indicating whether the conditional expectations in the E-step should be computed approximately or exactly.
X	the matrix with the observed covariate values (including a column of ones for the intercept)
groups	a vector indicating to which group each covariate belongs
lambda	the level of sparsity penalization
w	group-specific weights for different penalization of different groups
tol	a convergence criterion
maxiter	the maximum allowed number of iterations (EM steps)
init	a list of initial values for the coefficient
report.prog	a logical. If TRUE then the number of inner loops required to complete the M step of the EM algorithm are returned after each EM step.

Value

Returns the estimator of the semiparametric additive model with group testing data

Examples

grouplasso_gt_data <- get_grouplasso_data(n = 1000, response = "gt")

grouplasso_gt.out <- grouplasso_gt(Y = grouplasso_gt_data$Y$I,
                                   Z = grouplasso_gt_data$Y$A,
                                   Se = grouplasso_gt_data$Y$Se,
                                   Sp = grouplasso_gt_data$Y$Sp,
                                   E.approx = grouplasso_gt_data$Y$E.approx,
                                   X = grouplasso_gt_data$X,
                                   groups = grouplasso_gt_data$groups,
                                   lambda = 1,
                                   w  = grouplasso_gt_data$w,
                                   tol = 1e-3,
                                   maxiter = 500,
                                   report.prog = TRUE)

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