Updating index coefficients using MIP — update

Updates index coefficients by solving a mixed integer program.

Usage

update_alpha(
  Y,
  X,
  num_pred,
  num_ind,
  index.ind,
  dgz,
  alpha_old,
  lambda0 = 1,
  lambda2 = 1,
  M = 10,
  TimeLimit = Inf,
  MIPGap = 1e-04,
  NonConvex = -1,
  verbose = FALSE
)

Arguments

Y: Column matrix of response.
X: Matrix of predictors (size adjusted to number of indices).
num_pred: Number of predictors.
num_ind: Number of indices.
index.ind: An integer vector that assigns group index for each predictor.
dgz: The tibble of derivatives of the estimated smooths from previous iteration.
alpha_old: Vector of index coefficients from previous iteration.
lambda0: Penalty parameter for L0 penalty.
lambda2: Penalty parameter for L2 penalty.
M: Big-M value to be used in MIP.
TimeLimit: A limit for the total time (in seconds) expended in a single MIP iteration.
MIPGap: Relative MIP optimality gap.
NonConvex: The strategy for handling non-convex quadratic objectives or non-convex quadratic constraints in Gurobi solver.
verbose: The option to print detailed solver output.

Value

A vector of normalised index coefficients.