fastWavelets (version 1.0.1)

n_boundary_coefs: Number of Boundary Coefficients

Description

This function calculates the number of boundary coefficients for a particular wavelet/scaling filter and decomposition level.

Usage

n_boundary_coefs(wavelet, decomp_level)

Value

Number of boundary coefficients [integer]

Arguments

wavelet

Scaling filter name (see Details below) [string]

decomp_level

Decomposition level [integer]

Details

The argument wavelet can take one of the following values:

c("haar", "d1", "sym1", "bior1.1", "rbio1.1", "d2", "sym2", "d3", "sym3", "d4", "d5", "d6", "d7", "d8", "d9", "d10", "d11", "sym4", "sym5", "sym6", "sym7", "sym8", "sym9", "sym10", "coif1", "coif2", "coif3", "coif4", "coif5", "bior1.3", "bior1.5", "bior2.2", "bior2.4", "bior2.6", "bior2.8", "bior3.1", "bior3.3", "bior3.5", "bior3.7", "bior3.9", "bior4.4", "bior5.5", "bior6.8", "rbio1.3", "rbio1.5", "rbio2.2", "rbio2.4", "rbio2.6", "rbio2.8", "rbio3.1", "rbio3.3", "rbio3.5", "rbio3.7", "rbio3.9", "rbio4.4", "rbio5.5", "rbio6.8", "la8", "la10", "la12", "la14", "la16", "la18", "la20", "bl14", "bl18", "bl20", "fk4", "fk6", "fk8", "fk14", "fk18", "fk22", "b3spline")

References

M. Basta (2014),Additive Decomposition and Boundary Conditions in Wavelet-Based Forecasting Approaches, Acta Oeconomica Pragensia, 2, pp. 48-70.

Quilty, J., & Adamowski, J. (2018). Addressing the incorrect usage of wavelet-based hydrological and water resources forecasting models for real-world applications with best practices and a new forecasting framework. Journal of Hydrology, 563, 336–353. https://doi.org/10.1016/j.jhydrol.2018.05.003

Percival, D. B. and A. T. Walden (2000) Wavelet Methods for Time Series Analysis, Cambridge University Press.

Examples

J <- 4 # decomposition level
wavelet <- 'b3spline' # wavelet filter
nbc <- n_boundary_coefs(wavelet, J) # number of boundary-effected coefficients at decomp_level J