sample_srs | sample_systematic | sample_strat | method = "Queinnec" | method = "random | sample_sys_strat | sample_nc | sample_clhs | sample_balanced | sample_ahels | sample_existing | sample_existing(type = "clhs") | sample_existing(type = "balanced") | sample_existing(type = "srs") | sample_existing(type = "strat")
Package: sgsR 1.5.0
sgsR: Structurally Guided Sampling
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.
Authors:
sgsR_1.5.0.tar.gz
sgsR_1.5.0.zip(r-4.7)sgsR_1.5.0.zip(r-4.6)sgsR_1.5.0.zip(r-4.5)
sgsR_1.5.0.tgz(r-4.6-any)sgsR_1.5.0.tgz(r-4.5-any)
sgsR_1.5.0.tar.gz(r-4.7-any)sgsR_1.5.0.tar.gz(r-4.6-any)
sgsR_1.5.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
sgsR/json (API)
| # Install 'sgsR' in R: |
| install.packages('sgsR', repos = c('https://tgoodbody.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tgoodbody/sgsr/issues
Pkgdown/docs site:https://tgoodbody.github.io
Last updated from:be8855e75e. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 210 | ||
| source / vignettes | OK | 308 | ||
| linux-release-x86_64 | OK | 211 | ||
| macos-release-arm64 | OK | 188 | ||
| macos-oldrel-arm64 | OK | 178 | ||
| windows-devel | OK | 164 | ||
| windows-release | OK | 157 | ||
| windows-oldrel | OK | 179 | ||
| wasm-release | OK | 138 |
Exports:ahels_nSampahels_thresholdallocate_equalallocate_existingallocate_existing_equalallocate_existing_manualallocate_existing_optimallocate_existing_propallocate_forceallocate_manualallocate_optimallocate_propcalculate_allocationcalculate_coobscalculate_distancecalculate_lhsOptcalculate_pcompcalculate_popcalculate_representationcalculate_sampsizeclassPlotextract_metricsextract_stratamask_accessmask_existingmat_covmat_covNBmat_quantplot_scattersample_ahelssample_balancedsample_clhssample_existingsample_ncsample_srssample_stratsample_sys_stratsample_systematicstrat_breaksstrat_kmeansstrat_mapstrat_polystrat_quantilesstrat_rule1strat_rule2
Dependencies:BalancedSamplingclassclassIntclhscliclustercpp11DBIdeldirdplyre1071farvergenericsggplot2gluegtableisobandKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixpillarpkgconfigplyrpolyclipproxypurrrR6rasterRColorBrewerRcppRcppArmadilloreshape2rlangs2S7SamplingBigDatascalessfspspatstat.dataspatstat.geomspatstat.univarspatstat.utilsstringistringrterratibbletidyrtidyselectunitsutf8vctrsviridisLitewithrwk
Sampling
Last update: 2025-06-18
Started: 2022-01-27
Calculating
calculate_representation() | calculate_distance | calculate_pcomp | calculate_sampsize | calculate_allocation | Proportional allocation | Optimal Allocation | Equal allocation | Manual allocation | Sample evaluation algorithms | calculate_coobs | Latin hypercube sampling evaluation algorithms | calculate_pop | calculate_lhsOpt
Last update: 2023-06-09
Started: 2022-01-27
sgsR
Algorithm structure | strat_* | sample_* | calculate_* & extract_* | Parameters | mraster | sraster | access | %>%
Last update: 2023-02-08
Started: 2022-01-27
Stratification
strat_kmeans | strat_quantiles | strat_breaks | strat_poly | strat_map
Last update: 2023-02-08
Started: 2022-01-27
