LossProduction {ImportanceIndice} | R Documentation |
Allows calculating loss of production per
loss source (L.P.L.S.) and its total, maximum estimated production (M.E.P.),
percentage of loss of production per loss source (Percentage_L.P.L.S.=P.L.P.L.S.)
and its total, n_per_sample, and attention level (A.L.).
Equations:
*L.P.L.S. = total n of the L.S. x R.P. of the L.S. Where R.P. is R2 x (1 - P)
when it is of the first degree, or R.P. = ((R2 x (1 - P))x(B2/B1) when it
is of the second degree. Where, R2 = determination coefficient and
P = significance of ANOVA, B1 = regression coefficient, and
B2 = regression coefficient (variable2), of the simple regression equation of the L.S.
*M.E.P. = Total production (P.) + SUM L.P.L.S.1 + ....L.P.L.S.n.
*Percentage_L.P.L.S. = (L.P.L.S./M.E.P.) x 100.
* n_per_sample is n per sample
*A.L. = (n of the L.S. per sample x 0.75)/Percentage_L.P.L.S..
Where, n of the L.S. per sample = n/(number of trees/evaluation frequency/years/number of plant parts evaluated).
In this case, the number of trees = 20; evaluation frequency = 12 months per year for leaves, trunks, and branches,
two months for bunches of flowers per year, and three months for bunches of fruits per year; years = three;
and the number of plant parts evaluated = 12 leaves, 12 bunches of flowers and/or fruits,
and one trunk per tree/evaluation. And, 0.75 = 1 percent of loss fruits x 0.75 (safety margin).
LossProduction(DataLossSource,Prod,Evaluation,SegurityMargen=0.75,
MaximumToleranceOfLossFruits=1)
DataLossSource |
It is an matrix object containing data from loss sources. |
Prod |
Matrix with a column containing the production data. |
Evaluation |
Matrix containing three lines with the number of evaluations performed on each individual, the number of months evaluated and the number of evaluations performed per month. Must have a column for each source of loss. |
SegurityMargen |
Segurity margen (default=0.75) |
MaximumToleranceOfLossFruits |
Maximum tolerance in percentage (default=1) |
The function returns several indices associated with the production loss.
Germano Leao Demolin-Leite (Instituto de Ciencias Agrarias da UFMG)
Alcinei Mistico Azevedo (Instituto de Ciencias Agrarias da UFMG)
EffectivenessOfSolution
, NonAttentionLevel
, LossSource
library(ImportanceIndice)
data("DataLossSource")
data("DataSolutionSource")
data("DataProduction")
data("DataNumberSamples")
Distribution_LossSource(DataLossSource)
Distribution_SolutionSource(DataSolutionSource)
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LS<-LossSource(DataLoss = DataLossSource,DataProd = DataProduction)
LS
LP<-LossProduction(Data=DataLossSource,Prod = DataProduction,
Evaluation=DataNumberSamples,
SegurityMargen=0.75,MaximumToleranceOfLossFruits=1)
LP
ES<-EffectivenessOfSolution(DataLossSource=DataLossSource,
DataSolutionSource=DataSolutionSource,Production=DataProduction)
ES