The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

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 method
• doSampling() 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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.