mrf_requirement {mrf}

Multiresolution Forecast Requirements

Description

Computes requirements for given model using insights of various published papers and the manuscript [Stier et al., 2021] which is currently in press.

Usage

mrf_requirement(UnivariateData, CoefficientCombination, Aggregation)

Arguments

UnivariateData

[1:n] Numerical vector with n values.

CoefficientCombination

[1:Scales+1] Numerical vector with numbers which are associated with wavelet levels. The last number is associated with the smooth level. Each number determines the number of coefficient used per level. The selection follows a specific scheme.

Aggregation

[1:Scales] Numerical vector carrying numbers whose index is associated with the wavelet level. The numbers indicate the number of time in points used for aggregation from the original time series.

Value

List of

MinLen

Integer minimum required length for model.

StartTraining

Integer indicating the index of time series at which the training equations can be built up.

NumberWeights

Number of weights required for building model.

NumberEquations

Number of equations which can be built with given data.

Author(s)

Quirin Stier

References

[Stier et al., 2021] Stier, Q.,Gehlert, T. and Thrun, M. C.: Multiresolution Forecasting for Industrial Applications, Processess, 2021.

Aussem, A., Campbell, J., and Murtagh, F. Waveletbased Feature Extraction and Decomposition Strategies for Financial Forecasting. International Journal of Computational Intelligence in Finance, 6,5-12, 1998.

Renaud, O., Starck, J.-L., and Murtagh, F. Prediction based on a Multiscale De- composition. International Journal of Wavelets, Multiresolution and Information Processing, 1(2):217-232. doi:10.1142/S0219691303000153, 2003.

Murtagh, F., Starck, J.-L., and Renaud, O. On Neuro-Wavelet Modeling. Decision Support Systems, 37(4):475-484. doi:10.1016/S0167-9236(03)00092-7, 2004.

Renaud, O., Starck, J.-L., and Murtagh, F. Wavelet-based combined Signal Filter- ing and Prediction. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 35(6):1241-1251. doi:10.1109/TSMCB.2005.850182, 2005.

Examples

data(entsoe)
UnivariateData = entsoe$value
mrf_requirement(UnivariateData, c(2,3,4), c(2,4))