varSYG | R Documentation |
varSYG
computes the Sen-Yates-Grundy
variance estimator.
varSYG(y = NULL, pikl, precalc = NULL)
y |
A (sparse) numerical matrix of the variable(s) whose variance of their total is to be estimated. |
pikl |
A numerical matrix of second-order inclusion probabilities. |
precalc |
A list of pre-calculated results (analogous to the one used by
|
varSYG
aims at being an efficient implementation of the
Sen-Yates-Grundy variance estimator for sampling designs with fixed sample
size. It should be especially useful when several variance estimations are
to be conducted, as it relies on (sparse) matrix linear algebra.
Moreover, in order to be consistent with varDT
, varSYG
has a precalc
argument allowing for the re-use of intermediary
results calculated once and for all in a pre-calculation step (see
varDT
for details).
if y
is not NULL
(calculation step) : a
numerical vector of size the number of columns of y.
if y
is
NULL
(pre-calculation step) : a list containing pre-calculated data
(analogous to the one used by varDT
).
varHT
from package sampling
varSYG
differs from sampling::varHT
in several ways:
The formula implemented in varSYG
is solely
the Sen-Yates-Grundy estimator, which is the one calculated
by varHT
when method = 2.
varSYG
introduces several optimizations:
matrixwise operations allow to estimate variance on several interest variables at once
Matrix::TsparseMatrix capability yields significant performance gains.
Martin Chevalier
library(sampling)
set.seed(1)
# Simple random sampling case
N <- 1000
n <- 100
y <- rnorm(N)[as.logical(srswor(n, N))]
pikl <- matrix(rep((n*(n-1))/(N*(N-1)), n*n), nrow = n)
diag(pikl) <- rep(n/N, n)
varSYG(y, pikl)
sampling::varHT(y = y, pikl = pikl, method = 2)
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