stratallo (version 3.0.1)

rdca_iter: Iterative RDCA Implementation

Description

Iterative implementation of the Recursive Domain-Controlled Allocation (RDCA) algorithm. Not tested.

Usage

rdca_iter(n, H_counts, N, S, rho, rho2 = NULL, ref_domain = 1L)

Arguments

n

(integerish(1))
total sample size \(n\). Must satisfy 0 < n <= sum(N).

H_counts

(integerish)
strata counts in each domain.

N

(integerish)
strata sizes \((N_{d,h},\, (d,h) \in \mathcal H)\).

S

(numeric)
standard deviations \((S_{d,h},\, (d,h) \in \mathcal H)\) of surveyed variable in strata.

rho

(numeric)
parameters \((\rho_d,\, d \in \mathcal D)\) of the optimization problem.

rho2

(numeric)
the square of rho (rho^2), provided to reduce potential loss of precision due to finite-precision arithmetic.

ref_domain

(integerish(1))
reference domain (denoted by j in the thesis).

Examples

H_counts <- c(2, 2, 3)
N <- c(140, 110, 135, 190, 200, 40, 70)
S <- sqrt(c(180, 20, 5, 4, 35, 9, 40))
total <- c(2, 3, 5)
kappa <- c(0.5, 0.2, 0.3)
rho <- total * sqrt(kappa)
(n <- dca_nmax(H_counts, N, S) - 1)

# experimental function (not exported) – examples skipped
if (FALSE) {
rdca_iter(n, H_counts, N, S, rho)
# 140.0000 103.6139 132.1970 166.4127 195.9701  19.8750  70.0000
}