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[Stable]

This function wraps the iteration procedure that allows you to estimate the weights for each proportional strata. This assumes to minimize the weighted squared length of the confidence interval.

Usage

update_weights_strat_wilson(
  vars,
  strata_qnorm,
  initial_weights,
  n_per_strata,
  max_iterations = 50,
  conf_level = 0.95,
  tol = 0.001
)

Arguments

vars

(numeric)
normalized proportions for each strata.

strata_qnorm

(numeric(1))
initial estimation with identical weights of the quantiles.

initial_weights

(numeric)
initial weights used to calculate strata_qnorm. This can be optimized in the future if we need to estimate better initial weights.

n_per_strata

(numeric)
number of elements in each strata.

max_iterations

(integer(1))
maximum number of iterations to be tried. Convergence is always checked.

conf_level

(proportion)
confidence level of the interval.

tol

(numeric(1))
tolerance threshold for convergence.

Value

A list of 3 elements: n_it, weights, and diff_v.

See also

For references and details see prop_strat_wilson().

Examples

vs <- c(0.011, 0.013, 0.012, 0.014, 0.017, 0.018)
sq <- 0.674
ws <- rep(1 / length(vs), length(vs))
ns <- c(22, 18, 17, 17, 14, 12)

update_weights_strat_wilson(vs, sq, ws, ns, 100, 0.95, 0.001)
#> $n_it
#> [1] 3
#> 
#> $weights
#> [1] 0.2067191 0.1757727 0.1896962 0.1636346 0.1357615 0.1284160
#> 
#> $diff_v
#> [1] 1.458717e-01 1.497223e-03 1.442189e-06
#>