[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.

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
#>