Package: NRMSampling 0.2.2

NRMSampling: Sampling Design and Estimation Methods for Natural Resource Management

Provides functions for probability and non-probability sampling design, sample selection, and population estimation tailored to natural resource management. Probability methods include simple random sampling, stratified sampling, systematic sampling, cluster sampling, and probability-proportional-to-size sampling. Non-probability methods include convenience, judgement-based, and quota sampling. Estimation functions cover means, totals, ratio estimators, regression estimators, and the unequal-probability estimator of Horvitz and Thompson (1952, <doi:10.2307/2280784>) for unequal-probability designs. Utilities support biomass, soil-loss, and carbon-stock estimation from field plots. Spatial extensions provide random, systematic, stratified, and raster-weighted sampling within geographic polygons using the 'sf' and 'terra' packages, with extraction of remote-sensing covariates at sample locations. Applications include forest inventory, soil erosion monitoring, watershed studies, and ecological field surveys.

Authors:Sadikul Islam [aut, cre]

NRMSampling_0.2.2.tar.gz
NRMSampling_0.2.2.zip(r-4.7)NRMSampling_0.2.2.zip(r-4.6)NRMSampling_0.2.2.zip(r-4.5)
NRMSampling_0.2.2.tgz(r-4.6-any)NRMSampling_0.2.2.tgz(r-4.5-any)
NRMSampling_0.2.2.tar.gz(r-4.7-any)NRMSampling_0.2.2.tar.gz(r-4.6-any)
NRMSampling_0.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
NRMSampling/json (API)
NEWS

# Install 'NRMSampling' in R:
install.packages('NRMSampling', repos = c('https://sadikulislamiasri-hub.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 428 downloads 34 exports 0 dependencies

Last updated from:e32b325c78. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK130
source / vignettesOK180
linux-release-x86_64OK130
macos-release-arm64OK114
macos-oldrel-arm64OK117
windows-develOK81
windows-releaseOK86
windows-oldrelOK80
wasm-releaseOK99

Exports:biomass_estimatecarbon_stock_estimatecluster_sampleconvenience_sampleestimate_ciestimate_meanestimate_seestimate_totalestimate_varianceextract_raster_valuesht_estimatorht_varianceplot_samplingplot_sampling_ggplot_summarypps_samplepurposive_samplequota_sampleraster_pps_sampleraster_stratified_sampleratio_estimatorregression_estimatorsampling_efficiencysoil_loss_estimatespatial_biomass_estimatespatial_cluster_samplespatial_random_samplespatial_stratified_samplespatial_systematic_samplesrs_samplestratified_estimatorstratified_samplesystematic_sampleto_sf_points

Dependencies:

NRMSampling: Comprehensive Framework for Sampling Design and Estimation in Natural Resource Management

Sadikul Islam

Rendered fromNRMSampling.Rmdusingknitr::rmarkdownon Jun 23 2026.

Last update: 2026-04-22
Started: 2026-04-22

Readme and manuals

Help Manual

Help pageTopics
NRMSampling: Sampling Design and Estimation for Natural Resource ManagementNRMSampling-package NRMSampling
Biomass Estimation from Field Plotsbiomass_estimate
Carbon Stock Estimationcarbon_stock_estimate
Cluster Samplingcluster_sample
Convenience Samplingconvenience_sample
Confidence Interval for the Population Meanestimate_ci
Sample Meanestimate_mean
Standard Error of the Sample Meanestimate_se
Population Total Estimatorestimate_total
Sample Varianceestimate_variance
Extract Raster Values at Sample Pointsextract_raster_values
Horvitz-Thompson (HT) Estimatorht_estimator
Variance of the Horvitz-Thompson Estimatorht_variance
Plot Sample Points (Base Graphics)plot_sampling
Plot Sample Points with ggplot2plot_sampling_gg
Summary Statistics for a Sampled NRM Plot Datasetplot_summary
PPS Samplingpps_sample
Purposive (Judgement) Samplingpurposive_sample
Quota Samplingquota_sample
Raster-Weighted PPS Spatial Samplingraster_pps_sample
Raster-Stratified Spatial Samplingraster_stratified_sample
Ratio Estimatorratio_estimator
Regression Estimatorregression_estimator
Simulated NRM Plot Datasetsample_nrm
Simulated Spatial NRM Datasetsample_spatial
Sampling Efficiency Comparisonsampling_efficiency
Soil Loss Estimation from Sample Plotssoil_loss_estimate
Spatial Biomass Estimation from sf Pointsspatial_biomass_estimate
Spatial Cluster Samplingspatial_cluster_sample
Spatial Random Sampling within a Polygonspatial_random_sample
Stratified Spatial Samplingspatial_stratified_sample
Systematic Grid Sampling within a Polygonspatial_systematic_sample
Simple Random Samplingsrs_sample
Stratified Mean Estimatorstratified_estimator
Stratified Samplingstratified_sample
Systematic Samplingsystematic_sample
Convert a Data Frame to an sf Point Objectto_sf_points