WFPBB {MSIMST} | R Documentation |
The function is implemented based on the WFPBB algorithm from (Gunawan et al. 2020).
WFPBB(y, w, N, n, verbatim)
y |
The index of survey data. |
w |
Survey weights. The summation of survey weights should equal the population size |
N |
The population size. |
n |
The sample size. |
verbatim |
TRUE/FALSE. This variable decides whether print the progress information to the console. |
The re-sampled index of survey data.
Gunawan D, Panagiotelis A, Griffiths W, Chotikapanich D (2020). “Bayesian weighted inference from surveys.” Australian & New Zealand Journal of Statistics, 62(1), 71–94. ISSN 1467-842X, doi:10.1111/anzs.12284.
set.seed(100)
output_data <- reg_simulation3(N = 5000,
ni_lambda= 8,
beta = c(rep(1,6),rep(0,4)),
beta_b = 1.5,
dsq = 0.1,
sigmasq = 0.5,
delta = 0.6,
nu = 5.89,
muz = 0,
rho = 36.0,
sigmasq_z = 0.6,
zeta0 = -1.8,
zeta1 = 0.1)
y <- output_data$y
X <- output_data$X
survey_weight <- output_data$survey_weight
# set the population size
population_N <- 5000
# set the sample size
n <- length(y)
# run the WFPBB algorithm
index_WFPBB <- WFPBB(y = 1:n,
w = survey_weight,
N = population_N,
n = n,
verbatim = FALSE)
print(head(index_WFPBB))