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IIProductionUnknown  

Analyzing Data Through of Percentage of Importance Indice (Production Unknown) and Its Derivations
View on CRAN: Click here


Download and install IIProductionUnknown package within the R console
Install from CRAN:
install.packages("IIProductionUnknown")

Install from Github:
library("remotes")
install_github("cran/IIProductionUnknown")

Install by package version:
library("remotes")
install_version("IIProductionUnknown", "0.0.3")



Attach the package and use:
library("IIProductionUnknown")
Maintained by
Alcinei Mistico Azevedo
[Scholar Profile | Author Map]
First Published: 2022-06-15
Latest Update: 2023-02-01
Description:
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) . 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) .
How to cite:
Alcinei Mistico Azevedo (2022). IIProductionUnknown: Analyzing Data Through of Percentage of Importance Indice (Production Unknown) and Its Derivations. R package version 0.0.3, https://cran.r-project.org/web/packages/IIProductionUnknown. Accessed 10 Apr. 2025.
Previous versions and publish date:
0.0.1 (2022-06-15 09:00), 0.0.2 (2022-10-12 01:12)
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