Description
Dynamic Survey Sampling Solutions.
Description
A robust solution employing the 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.
README.md
samplingin
Overview
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.
Installation
install.packages("samplingin")
Usage
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