Weight {EEML} | R Documentation |
Selection of Superior Models Using MSC Algorithm
Description
Selection of Superior Models Using MSC Algorithm
Usage
Weight(ModelSel, Optim = "PSO")
Arguments
ModelSel |
Dataframe of predicted values of selected models with first column as actual values |
Optim |
Optimisation technique |
Value
WeightEn: Ensemble weight of the candidate models
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
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")
[Package EEML version 0.1.0 Index]