WASP1.4.4 package

Wavelet System Prediction

data.gen.ar1

Generate predictor and response data from AR1 model.

data.gen.ar4

Generate predictor and response data from AR4 model.

data.gen.ar9

Generate predictor and response data from AR9 model.

at.vt

Variance Transformation Operation - AT(a trous)

at.vt.val

Variance Transformation Operation for Validation

at.wd

a trous (AT) based additive decompostion using Daubechies family wavel...

data.gen.HL

Generate predictor and response data: Hysteresis Loop

data.gen.Rossler

Generate predictor and response data: Rossler system

data.gen.SW

Generate predictor and response data: Sinewave model

data.gen.tar1

Generate predictor and response data from TAR1 model.

data.gen.tar2

Generate predictor and response data from TAR2 model.

scal2freqR

Scale to frequency by R

SPI.calc

Calculate Standardized Precipitation Index, SPI

dwt.vt

Variance Transformation Operation - MRA

dwt.vt.val

Variance Transformation Operation for Validation

fig.dwt.vt

Plot function: Variance structure before and after variance transforma...

knn

Modified k-nearest neighbour conditional bootstrap or regression funct...

knnregl1cv

Leave one out cross validation.

modwt.vt

Variance Transformation Operation - MODWT

stepwise.VT

Calculate stepwise high order VT in calibration

modwt.vt.val

Variance Transformation Operation for Validation

mra.plot

Plot function: Plot original time series and decomposed frequency comp...

non.bdy

Replace Boundary Wavelet Coefficients with Missing Values (NA).

padding

Padding data to dyadic sample size

pic.calc

Calculate PIC

r2.boot

R2 threshold by re-sampling approach

scal2freqM

Scale to frequency by Matlab

stepwise.VT.val

Calculate stepwise high order VT in validation

WASP-package

WASP: WAvelet System Prediction

wave.var

Produces an estimate of the multiscale variance along with approximate...

The wavelet-based variance transformation method is used for system modelling and prediction. It refines predictor spectral representation using Wavelet Theory, which leads to improved model specifications and prediction accuracy. Details of methodologies used in the package can be found in Jiang, Z., Sharma, A., & Johnson, F. (2020) <doi:10.1029/2019WR026962>, Jiang, Z., Rashid, M. M., Johnson, F., & Sharma, A. (2020) <doi:10.1016/j.envsoft.2020.104907>, and Jiang, Z., Sharma, A., & Johnson, F. (2021) <doi:10.1016/J.JHYDROL.2021.126816>.

  • Maintainer: Ze Jiang
  • License: GPL-3
  • Last published: 2024-07-20