PWEV {PWEV}

PSO Based Weighted Ensemble Algorithm for Volatility Modelling

Description

PSO Based Weighted Ensemble Algorithm for Volatility Modelling

Usage

PWEV(Data, SplitR)

Arguments

Data

Univariate Time Series Data

SplitR

Split Ratio

Value

• TrainFitted: Fitted values for the train series

• TestPred: Prediction for the test series

• Accuracy: Accuracy metric of the proposed model

• Weights: Weights of the ensemble

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("PWEV")
data<- as.ts(rnorm(200,100,50))
Result <- PWEV(data, 0.9)