bestimate: Bayesian finite population with BART and FPBB

In awmercer/bestimate: Bayesian Finite Population Survey Estimation With FPBB and BART

Description

Bayesian finite population with BART and FPBB

Usage

bestimate(samp, ref, y_var_names, x_var_names, sp_wts = NULL,
  propensity = TRUE, prediction = TRUE, double_robust_wt = TRUE,
  double_robust_reg = TRUE, dr_propensity_transform = log,
  propensity_replicates = 1, quality_measures = TRUE,
  pred_subsample_size = 10000, posterior_draws = 1000,
  bart_params = list(mc.cores = 1, ntree = 50))

Arguments

samp	data.frame containing the survey sample data.
ref	data.frame containing the reference sample.
y_var_names	Character vector containing names of the outcome variables.
x_var_names	Character vector containing names of the covariates
posterior_draws	Number of posterior draws
sp_wt_frame	data.frame containing one column of weights for each synthetic population.

Value

Good question

awmercer/bestimate documentation built on May 22, 2019, 8:50 p.m.