Package: kbaabb 0.0.1

kbaabb: Generates an Artificial Population Based on the KBAABB Methodology

Provides tools for generating an artificial population based on a kNN-based approximation to the approximate Bayesian bootstrap (KBAABB). This methodology is described in White et al. (2025) <doi:10.1093/forestry/cpaf071>.

Authors:Grayson W. White [aut, cre], Jerzy A. Wieczorek [aut], Leland Russell [aut], Samantha Schroeder [aut], Tracey S. Frescino [aut], Kelly S. McConville [aut]

kbaabb_0.0.1.tar.gz
kbaabb_0.0.1.zip(r-4.7-any)kbaabb_0.0.1.zip(r-4.6-any)kbaabb_0.0.1.zip(r-4.5-any)
kbaabb_0.0.1.tgz(r-4.6-any)kbaabb_0.0.1.tgz(r-4.5-any)
kbaabb_0.0.1.tar.gz(r-4.7-any)kbaabb_0.0.1.tar.gz(r-4.6-any)
kbaabb_0.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
kbaabb/json (API)

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

Bug tracker:https://github.com/graysonwhite/kbaabb/issues

Datasets:
  • SJC_boundary - Polygon boundary dataset for San Juan County, Washington, USA
  • SJC_population - Population dataset for San Juan County, Washington, USA
  • SJC_sample - Sample dataset for San Juan County, Washington, USA

On CRAN:

Conda:

4.08 score 4 stars 1 scripts 1 exports 1 dependencies

Last updated from:614b24cd61. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK124
source / vignettesOK188
linux-releaseOK112
macos-releaseOK209
macos-oldrelOK199
windows-develOK69
windows-releaseOK63
windows-oldrelOK50
wasm-releaseOK82

Exports:kbaabb

Dependencies:FNN