CRAN/E | IIProductionUnknown

IIProductionUnknown

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

Installation

About

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) doi:10.1590/1519-6984.253218.

Key Metrics

Version 0.0.3
Published 2023-02-01 450 days ago
Needs compilation? no
License GPL-3
CRAN checks IIProductionUnknown results
Language en-US

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Maintainer

Maintainer

Alcinei Mistico Azevedo

alcineimistico@hotmail.com

Authors

Germano Leao Demolin-Leite

aut

Alcinei Mistico Azevedo

aut / cre

Material

NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

IIProductionUnknown archive

Depends

crayon