do_combination: Workhorse function for creating a synthetic estimator by...

Description Usage Arguments Value

View source: R/do_combination.R

Description

Creates a synthetic estimator by minimizing the (estimated) mean squared error of a linear combination of multiple candidate estimators.

Usage

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do_combination(
  ests,
  name_0,
  C,
  print = FALSE,
  exclude_t0 = FALSE,
  bias_type = "raw_diff",
  boot_mean = NULL,
  ate_0 = NULL,
  n = NULL
)

Arguments

ests

one-row, p-column data frame of estimators.

name_0

character value of the name of the presumed unbiased estimator, θ_0. Default is NULL, which returns results for using each candidate estimator as θ_0, one synthetic estimator for each. If ate_0 is given, then it is used as θ_0 in place of this.

C

p x p covariance matrix of ests.

print

logical indicating whether details should be printed. Default is FALSE.

exclude_t0

logical indicating whether θ_0 should be considered an external estimator (not a candidate for combining with others). Default is FALSE.

bias_type

method to compute the bias in the mean squard error. Default is raw_diff, which computes the bias as the raw difference between each of the candidate estimator and θ_0. Other options to compute the bias include: bootstrap which computes the bias as the difference between the mean of the bootstrap samples and the observed value of θ_0; bootstrap_all which computes the bias as the mean of the difference between the bootstrapped version of the candidate estimator and the bootstrapped version of θ_0; none which assumes no bias; shrunk which computes the bias as the raw difference divided by n.

boot_mean

mean of bootstrap samples for bootstrap-based bias estimation.

ate_0

external value of θ_0. Default is NULL, in which case θ_0 is taken to be name_0.

n

sample size. Default is NULL. Needed only if bias_type is shrunk.

Value

list of three objects, including ate_res which gives results for the synthetic estimator, b_res which gives results for how the estimators were combined, and C which gives the covariance matrix of the estimators.


denisagniel/synthate documentation built on April 16, 2020, 12:45 a.m.