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sgsR
View on CRAN: Click
here
Download and install sgsR package within the R console
Install from CRAN:
install.packages("sgsR")
Install from Github:
library("remotes")
install_github("cran/sgsR")
Install by package version:
library("remotes")
install_version("sgsR", "1.4.5")
Attach the package and use:
library("sgsR")
Maintained by
Tristan RH Goodbody
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.sgsR . https://github.com/tgoodbody/sgsR/issues . https://github.com/tgoodbody/sgsR . https://tgoodbody.github.io/sgsR/ . sgsR citation info . sgsR results . sgsR.pdf . sgsR . sgsR_1.4.5.tar.gz . sgsR_1.4.5.zip . sgsR_1.4.5.zip . sgsR_1.4.5.zip . sgsR_1.4.5.tgz . sgsR_1.4.5.tgz . sgsR_1.4.5.tgz . sgsR_1.4.5.tgz . sgsR_1.4.5.tgz . sgsR_1.4.5.tgz . sgsR archive . https://CRAN.R-project.org/package=sgsR .
First Published: 2022-06-24
Latest Update: 2023-06-13
Description:
Structurally guided sampling (SGS) approaches for airborne laser scanning (ALS; LIDAR). Primary functions provide means
to generate data-driven stratifications & methods for allocating samples. Intermediate functions for calculating and extracting important information
about input covariates and samples are also included. Processing outcomes are intended to help forest and environmental management
practitioners better optimize field sample placement as well as assess and augment existing sample networks in the context of data
distributions and conditions. ALS data is the primary intended use case, however any rasterized remote sensing data can be used,
enabling data-driven stratifications and sampling approaches.
How to cite:
Tristan RH Goodbody (2022). sgsR: Structurally Guided Sampling. R package version 1.4.5, https://cran.r-project.org/web/packages/sgsR. Accessed 29 Mar. 2025.
Previous versions and publish date:
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Other R packages that sgsR depends,
imports, suggests or enhances
Complete documentation for sgsR
Functions, R codes and Examples using
the sgsR R package
Some associated functions: allocating . calculate_allocation . calculate_allocation_existing . calculate_coobs . calculate_distance . calculate_lhsOpt . calculate_pcomp . calculate_pop . calculate_representation . calculate_sampsize . check_existing . coords_existing . extract_metrics . extract_strata . masking . matrices . plot . prepare_existing . rules . sample_ahels . sample_balanced . sample_clhs . sample_existing . sample_existing_balanced . sample_existing_clhs . sample_existing_srs . sample_existing_strat . sample_nc . sample_srs . sample_strat . sample_sys_strat . sample_systematic . sgsR-package . strat_breaks . strat_kmeans . strat_map . strat_poly . strat_quantiles . take_samples . vectorize . write .
Some associated R codes: calculate_allocation.R . calculate_allocation_existing.R . calculate_coobs.R . calculate_distance.R . calculate_lhsOpt.R . calculate_pcomp.R . calculate_pop.R . calculate_representation.R . calculate_sampsize.R . extract_metrics.R . extract_strata.R . sample_ahels.R . sample_balanced.R . sample_clhs.R . sample_existing.R . sample_existing_balanced.R . sample_existing_clhs.R . sample_existing_srs.R . sample_existing_strat.R . sample_nc.R . sample_srs.R . sample_strat.R . sample_sys_strat.R . sample_systematic.R . sgsR-package.R . strat_breaks.R . strat_kmeans.R . strat_map.R . strat_poly.R . strat_quantiles.R . utils-allocation-existing.R . utils-allocation.R . utils-existing.R . utils-mask.R . utils-mat.R . utils-plot.R . utils-samplerules.R . utils-vectorization.R . utils-write.R . zzz.R . Full sgsR package functions and examples
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