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NRMSampling  

Sampling Design and Estimation Methods for Natural Resource Management
View on CRAN: Click here


Download and install NRMSampling package within the R console
Install from CRAN:
install.packages("NRMSampling")

Install from Github:
library("remotes")
install_github("cran/NRMSampling")

Install by package version:
library("remotes")
install_version("NRMSampling", "0.2.2")



Attach the package and use:
library("NRMSampling")
Maintained by
Sadikul Islam
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-22
Latest Update: 2026-04-22
Description:
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.
How to cite:
Sadikul Islam (2026). NRMSampling: Sampling Design and Estimation Methods for Natural Resource Management. R package version 0.2.2, https://cran.r-project.org/web/packages/NRMSampling. Accessed 24 Oct. 2026.
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