ModelSel: Selection of Superior Models Using MSC Algorithm

In EEML: Ensemble Explainable Machine Learning Models

Selection of Superior Models Using MSC Algorithm

Description

Selection of Superior Models Using MSC Algorithm

Usage

ModelSel(df, Alpha, K)

Arguments

df	Dataframe of predicted values of models with first column as actual values
Alpha	Confidence level of MCS tests
K	Resampling length

Value

• SelModel: Name of the selected 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.

• Hansen PR, Lunde A, Nason JM, 2011. The model confidence set. Econometrica, 79(2), 453-497

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))
Model4<- as.ts(rnorm(200,100,50))
Model5<- as.ts(rnorm(200,100,50))
DF <- cbind(Actual, Model1,Model2,Model3,Model4,Model5)
SelModel<-ModelSel(df=DF, Alpha=0.2, K=1000)

EEML documentation built on Sept. 11, 2024, 6:54 p.m.