Package: BLA 1.0.1.9000

BLA: Boundary Line Analysis

Fits boundary line models to datasets as proposed by Webb (1972) <doi:10.1080/00221589.1972.11514472> and makes statistical inferences about their parameters. Provides additional tools for testing datasets for evidence of boundary presence and selecting initial starting values for model optimization prior to fitting the boundary line models. It also includes tools for conducting post-hoc analyses such as predicting boundary values and identifying the most limiting factor (Miti, Milne, Giller, Lark (2024) <doi:10.1016/j.fcr.2024.109365>). This ensures a comprehensive analysis for datasets that exhibit upper boundary structures.

Authors:Chawezi Miti [cre, aut, cph], Richard M Lark [aut], Alice E Milne [aut], Ken E Giller [aut], Victor O Sadras [ctb], University of Nottingham/Rothamsted Research [fnd]

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BLA.pdf |BLA.html
BLA/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/chawezimiti/bla/issues

Datasets:

On CRAN:

5.26 score 1 stars 11 scripts 590 downloads 16 exports 35 dependencies

Last updated 6 days agofrom:0434f57acd. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 18 2024
R-4.5-winOKNov 18 2024
R-4.5-linuxOKNov 18 2024
R-4.4-winOKNov 18 2024
R-4.4-macOKNov 18 2024
R-4.3-winOKNov 18 2024
R-4.3-macOKNov 18 2024

Exports:APblbinble_profileblqrbolidescbvnexpl_boundarykurtlimfactorna.dropocskewpredictBLseHessianskewstartValuessummastat

Dependencies:classclassIntcliconcavemancurldata.tableDBIdplyre1071fansigenericsgluejsonliteKernSmoothlifecyclemagrittrMASSmvtnormnumDerivpillarpkgconfigproxyR6Rcpprlangs2sftibbletidyselectunitsutf8V8vctrswithrwk

Boundary Line Analysis

Rendered fromBLA.Rmdusingknitr::rmarkdownon Nov 18 2024.

Last update: 2024-05-27
Started: 2024-04-04

Introduction to boundary line analysis

Rendered fromIntroduction_to_BLA.Rmdusingknitr::rmarkdownon Nov 18 2024.

Last update: 2024-05-27
Started: 2024-04-04

Use of censored bivariate normal model function for yield gap analysis

Rendered fromCensored_bivariate_normal_model.Rmdusingknitr::rmarkdownon Nov 18 2024.

Last update: 2024-05-23
Started: 2024-04-04