update_alpha: Updating index coefficients using MIP

In smimodel: Sparse Multiple Index Models for Nonparametric Forecasting

Updating index coefficients using MIP

Description

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.

smimodel documentation built on April 8, 2026, 5:06 p.m.