cov_nnls function

Estimate non-negative diagonal terms on G matrix

Helper function for G_estimate. Uses least squares under non-negativity constraints, mainly relying on nnls capability from lsei.

cov_nnls(
  data,
  L,
  out_index,
  data_cov,
  RE_table,
  idx_lst,
  designmat,
  betaHat,
  GTilde,
  non_neg = 0,
  silent = TRUE
)

Arguments

• data: Data frame containing all predictor and outcome variables
• L: The dimension of the functional domain
• out_index: Indices of outcome variables in data
• data_cov: (unsure) Covariance of variables
• RE_table: Data frame containing random effects and interactions
• idx_lst: (unsure) Column indices of random effects
• designmat: (unsure)
• betaHat: Estimates of coefficients of random effects
• GTilde: Current GTilde estimate, created as an intermediate in G_estimate
• non_neg: (unsure), defaults to 0
• silent: Whether to print the step. Defaults to TRUE.

Returns

A matrix with the same dimensions as GTilde.