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Model-based prediction of design variances (Ospats family)

Source: R/brus_native.R
morie_ospats.Rd

Equations 13.5, 13.7, 13.10, 13.12, and print equations 13.15 to 13.17 of Brus (2022). The print edition tags E_xi of the stratum variance as 13.16 (untagged on the web) and the Ospats objective as 13.17 (web 13.16).

Usage

morie_ospats(
  gamma_bar_h = NULL,
  weights = NULL,
  n_h = NULL,
  n = NA,
  s_h = NULL,
  c_h = NULL,
  zhat_i = NA,
  zhat_j = NA,
  r2 = NA,
  s2_i = NA,
  s2_j = NA,
  s2_ij = NA,
  d2_upper_sum = NA,
  n_h_units = NA,
  per_stratum_sums = NULL,
  n_population = NA
)

Arguments

gamma_bar_h

Mean semivariances.

weights, n_h

Strata.

n

Total sample size.

s_h, c_h

Allocation pieces.

zhat_i, zhat_j, r2, s2_i, s2_j, s2_ij

Pairwise pieces.

d2_upper_sum, n_h_units

Stratum-variance pieces.

per_stratum_sums, n_population

Objective pieces.

Value

List with stsi_variance, equal_area_variance, alloc_variance, objective_o, d2, stratum_variance, ospats_objective (as supplied).

Examples

morie_ospats()
#> list()