lm_robust_fit function

Internal method that creates linear fits

lm_robust_fit(
  y,
  X,
  yoriginal = NULL,
  Xoriginal = NULL,
  weights,
  cluster,
  fixed_effects = NULL,
  ci = TRUE,
  se_type,
  has_int,
  alpha = 0.05,
  return_vcov = TRUE,
  return_fit = TRUE,
  try_cholesky = FALSE,
  iv_stage = list(0)
)

Arguments

• y: numeric outcome vector
• X: numeric design matrix
• yoriginal: numeric outcome vector, unprojected if there are fixed effects
• Xoriginal: numeric design matrix, unprojected if there are fixed effects. Any column named "(Intercept)" will be dropped
• weights: numeric weights vector
• cluster: numeric cluster vector
• fixed_effects: character matrix of fixed effect groups
• ci: boolean that when T returns confidence intervals and p-values
• se_type: character denoting which kind of SEs to return
• has_int: logical, whether the model has an intercept, used for $R^2$
• alpha: numeric denoting the test size for confidence intervals
• return_vcov: logical, whether to return the vcov matrix for later usage
• return_fit: logical, whether to return fitted values
• try_cholesky: logical, whether to try using a cholesky decomposition to solve LS instead of a QR decomposition
• iv_stage: list of length two, the first element denotes the stage of 2SLS IV estimation, where 0 is used for OLS. The second element is only used for the second stage of 2SLS and has the first stage design matrix. For OLS, the default, list(0), for the first stage of 2SLS list(1), for second stage of 2SLS list(2, first_stage_design_mat).