IIProductionUnknown: Analyzing Data Through of Percentage of Importance Indice (Production Unknown) and Its Derivations

The Importance Index (I.I.) can determine the loss and solution sources for a system in certain knowledge areas (e.g., agronomy), when production (e.g., fruits) is known (Demolin-Leite, 2021). Events (e.g., agricultural pest) can have different magnitudes (numerical measurements), frequencies, and distributions (aggregate, random, or regular) of event occurrence, and I.I. bases in this triplet (Demolin-Leite, 2021) <https://cjascience.com/index.php/CJAS/article/view/1009/1319>. Usually, the higher the magnitude and frequency of aggregated distribution, the greater the problem or the solution (e.g., natural enemies versus pests) for the system (Demolin-Leite, 2021). However, the final production of the system is not always known or is difficult to determine (e.g., degraded area recovery). A derivation of the I.I. is the percentage of Importance Index-Production Unknown (% I.I.-PU) that can detect the loss or solution sources, when production is unknown for the system (Demolin-Leite, 2024) <doi:10.1590/1519-6984.253218>.

Version: 0.0.1
Depends: crayon
Published: 2022-06-15
Author: Germano Leao Demolin-Leite ORCID iD [aut], Alcinei Mistico Azevedo ORCID iD [aut, cre]
Maintainer: Alcinei Mistico Azevedo <alcineimistico at hotmail.com>
License: GPL-3
NeedsCompilation: no
Language: en-US
Materials: NEWS
CRAN checks: IIProductionUnknown results


Reference manual: IIProductionUnknown.pdf


Package source: IIProductionUnknown_0.0.1.tar.gz
Windows binaries: r-devel: IIProductionUnknown_0.0.1.zip, r-release: IIProductionUnknown_0.0.1.zip, r-oldrel: IIProductionUnknown_0.0.1.zip
macOS binaries: r-release (arm64): IIProductionUnknown_0.0.1.tgz, r-oldrel (arm64): IIProductionUnknown_0.0.1.tgz, r-release (x86_64): IIProductionUnknown_0.0.1.tgz, r-oldrel (x86_64): IIProductionUnknown_0.0.1.tgz


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