EEML (version 0.1.1)

Weight: Selection of Superior Models Using MSC Algorithm

Description

Selection of Superior Models Using MSC Algorithm

Usage

Weight(ModelSel, Optim = "PSO")

Value

• WeightEn: Ensemble weight of the candidate models

Arguments

ModelSel

Dataframe of predicted values of selected models with first column as actual values

Optim

Optimisation technique

References

• Paul, R.K., Das, T. and Yeasin, M., 2023. Ensemble of time series and machine learning model for forecasting volatility in agricultural prices. National Academy Science Letters, 46(3), pp.185-188.

• Yeasin, M. and Paul, R.K., 2024. OptiSembleForecasting: optimization-based ensemble forecasting using MCS algorithm and PCA-based error index. The Journal of Supercomputing, 80(2), pp.1568-1597.

Examples

# \donttest{
library("EEML")
Actual<- as.ts(rnorm(200,100,50))
Model1<- as.ts(rnorm(200,100,50))
Model2<- as.ts(rnorm(200,100,50))
Model3<- as.ts(rnorm(200,100,50))
DF <- cbind(Actual, Model1,Model2,Model3)
SelModel<-Weight(ModelSel=DF,Optim="PSO")
# }