ModelSel {EEML} | R Documentation |
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=NULL)
[Package EEML version 0.1.0 Index]