Package: IIProductionUnknown
Type: Package
Title: Analyzing Data Through of Percentage of Importance Indice
        (Production Unknown) and Its Derivations
Version: 0.0.3
Authors@R: 
     c(person(given = "Germano Leao",
           family = "Demolin-Leite",
           role = "aut",
           email = "germano.demolin@gmail.com",
           comment = c(ORCID = "0000-0002-2928-3193")),
     person(given = "Alcinei Mistico",
           family = "Azevedo",
           role = c("aut", "cre"),
           email = "alcineimistico@hotmail.com",
           comment = c(ORCID = "0000-0001-5196-0851")))       
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) <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>. 
License: GPL-3
Depends: crayon
Encoding: UTF-8
Language: en-US
LazyData: false
RoxygenNote: 7.2.2
NeedsCompilation: no
Packaged: 2023-02-01 12:12:19 UTC; User
Author: Germano Leao Demolin-Leite [aut]
    (<https://orcid.org/0000-0002-2928-3193>),
  Alcinei Mistico Azevedo [aut, cre]
    (<https://orcid.org/0000-0001-5196-0851>)
Maintainer: Alcinei Mistico Azevedo <alcineimistico@hotmail.com>
Repository: CRAN
Date/Publication: 2023-02-01 12:40:05 UTC
Built: R 4.4.3; ; 2025-10-13 09:32:51 UTC; windows
