samplingin is a robust solution employing SRS (Simple Random Sampling), systematic and PPS (Probability Proportional to Size) sampling methods, ensuring a methodical and representative selection of data. Seamlessly allocate predetermined allocations to smaller levels.
get_allocation() allocate predetermined allocations to smaller levels using proportional allocation methoddoSampling() samples selection using srs, systematic or PPS (Probability Proportional to Size) sampling method based on certain allocation.library(samplingin)
library(magrittr)
library(dplyr)
contoh_alokasi = alokasi_dt %>%
select(-n_primary) %>%
mutate(nasional = 1)
alokasi_dt = get_allocation(
data = contoh_alokasi
, alokasi = 100
, group = c("nasional")
, pop_var = "jml_kabkota"
)
# Simple Random Sampling (SRS)
dtSampling_srs = doSampling(
pop = pop_dt
, alloc = alokasi_dt
, nsample = "n_primary"
, type = "U"
, ident = c("kdprov")
, method = "srs"
, auxVar = "Total"
, seed = 7892
)
# Population data with flag sample
pop_dt = dtSampling_srs$pop
# Selected Samples
dsampel = dtSampling_srs$sampledf
# Details of sampling process
rincian = dtSampling_srs$details
# PPS Sampling
dtSampling_pps = doSampling(
pop = pop_dt
, alloc = alokasi_dt
, nsample = "n_primary"
, type = "U"
, ident = c("kdprov")
, method = "pps"
, auxVar = "Total"
, seed = 1234
)
# Population data with flag sample
pop_dt = dtSampling_pps$pop
# Selected Samples
sampledf = dtSampling_pps$sampledf
# Details of sampling process
details = dtSampling_pps$details
# Systemtic Sampling
dtSampling_sys = doSampling(
pop = pop_dt
, alloc = alokasi_dt
, nsample = "n_primary"
, type = "U"
, ident = c("kdprov")
, method = "systematic"
, seed = 4321
)
# Population data with flag sample
pop_dt = dtSampling_sys$pop
# Selected Samples
sampledf = dtSampling_sys$sampledf
# Details of sampling process
details = dtSampling_sys$details
# Systematic Sampling (Secondary Samples)
alokasi_dt_p = alokasi_dt %>%
mutate(n_secondary = 2 * n_primary)
dtSampling_sys_p = doSampling(
pop = dtSampling_sys$pop
, alloc = alokasi_dt_p
, nsample = "n_secondary"
, type = "P"
, ident = c("kdprov")
, method = "systematic"
, seed = 6789
, is_secondary = TRUE
)
# Population data with flag sample
pop_dt = dtSampling_sys_p$pop
# Selected Samples
dsampel = dtSampling_sys_p$sampledf
# Details of sampling process
rincian = dtSampling_sys_p$details
# Systematic Sampling with predetermined random number (predetermined_rn parameter)
alokasi_dt_rn = alokasi_dt %>% rowwise() %>% mutate(ar = runif(n(),0,1)) %>% ungroup
dtSampling_sys = doSampling(
pop = pop_dt
, alloc = alokasi_dt_rn
, nsample = "n_primary"
, type = "U"
, ident = c("kdprov")
, method = "systematic"
, predetermined_rn = "ar"
, seed = 4321
)
# Population data with flag sample
pop_dt = dtSampling_sys$pop
# Selected Samples
sampledf = dtSampling_sys$sampledf
# Details of sampling process
details = dtSampling_sys$details