stratallo (version 3.0.1)

rna_experimental: RNA – Experimental Versions

Description

Experimental variants of the Recursive Neyman Algorithm (RNA).

Usage

rna_rec(
  total_cost,
  A,
  bounds = NULL,
  unit_costs = rep(1, length(A)),
  cmp = .Primitive(">=")
)
rna_prior(
  total_cost,
  A,
  bounds = NULL,
  check = NULL,
  cmp = .Primitive(">="),
  details = FALSE
)

Arguments

total_cost

(numeric(1))
total survey cost \(c\). Must be strictly positive. Additionally:

• If one-sided lower bounds \(m_1, \ldots, m_H\) are imposed, it is required that \(c \geq \sum_{h=1}^H c_h m_h\), i.e. total_cost >= sum(unit_costs * bounds).

• If one-sided upper bounds \(M_1, \ldots, M_H\) are imposed, it is required that \(c \leq \sum_{h=1}^H c_h M_h\), i.e. total_cost <= sum(unit_costs * bounds).

A

(numeric)
population constants \(A_1,\ldots,A_H\). All values must be strictly positive.

bounds

(numeric or NULL)
optional lower bounds \(m_1,\ldots,m_H\), or upper bounds \(M_1,\ldots,M_H\), or NULL to indicate that no inequality constraints are imposed. If not NULL, bounds is interpreted as:

• lower bounds, if cmp = .Primitive("<="), or

• upper bounds, if cmp = .Primitive(">=").

See also total_cost.

unit_costs

(numeric)
costs \(c_1,\ldots,c_H\) of surveying one element in each stratum. Strictly positive values. May also be of length 1, in which case the value is recycled to match the length of bounds.

cmp

(function)
a binary comparison operator used to check for violations of bounds. Must be either .Primitive("<=") (treating bounds as lower bounds and invoking the LRNA algorithm) or .Primitive(">=") (treating bounds as upper bounds and invoking the RNA algorithm).

The value of this argument has no effect if bounds is NULL.

check

(integer)
indices of strata for which allocation constraints may be violated. For all other strata, constraint violations are not checked.

details

(logical(1))
should detailed information on stratum assignments (either take-Neyman or take-bound), values of the set function \(s\), and the number of iterations be included in the output?

Functions

• rna_rec(): Recursive implementation of the RNA.

• rna_prior(): A variant of the Recursive Neyman Algorithm (RNA) that uses prior information about strata for which allocation constraints may be violated. For all other strata, allocations are assumed to satisfy the bounds.

Examples

A <- c(3000, 4000, 5000, 2000)
M <- c(100, 90, 70, 80) # upper bounds

# experimental function (not exported) – examples skipped
if (FALSE) {
rna_rec(total_cost = 190, A = A, bounds = M)
rna_rec(total_cost = 312, A = A, bounds = M)
rna_rec(total_cost = 339, A = A, bounds = M)
rna_rec(total_cost = 340, A = A, bounds = M)
}