Sigma_cal: Variance-covariance matrix of the estimation equation

In ipd: Inference on Predicted Data

Variance-covariance matrix of the estimation equation

Description

Sigma_cal function for variance-covariance matrix of the estimation equation

Usage

Sigma_cal(
  X_lab,
  X_unlab,
  Y_lab,
  Yhat_lab,
  Yhat_unlab,
  w,
  theta,
  quant = NA,
  method
)

Arguments

X_lab	Array or data.frame containing observed covariates in labeled data.
X_unlab	Array or data.frame containing observed or predicted covariates in unlabeled data.
Y_lab	Array or data.frame of observed outcomes in labeled data.
Yhat_lab	Array or data.frame of predicted outcomes in labeled data.
Yhat_unlab	Array or data.frame of predicted outcomes in unlabeled data.
w	weights vector PSPA linear regression (d-dimensional, where d equals the number of covariates).
theta	parameter theta
quant	quantile for quantile estimation
method	indicates the method to be used for M-estimation. Options include "mean", "quantile", "ols", "logistic", and "poisson".

Value

variance-covariance matrix of the estimation equation

ipd documentation built on April 4, 2025, 4:41 a.m.