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Sie2nts (version 0.1.0)

Sieve Methods for Non-Stationary Time Series

Description

We provide functions for estimation and inference of locally-stationary time series using the sieve methods and bootstrapping procedure. In addition, it also contains functions to generate Daubechies and Coiflet wavelet by Cascade algorithm and to process data visualization.

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Version

Install

install.packages('Sie2nts')

Monthly Downloads

183

Version

0.1.0

License

MIT + file LICENSE

Maintainer

Xiucai Ding

Last Published

January 18th, 2023

Functions in Sie2nts (0.1.0)

sie.plot.pacf

Plot Partial Autocorrelation Function (PACF)
sie.predict

Predicting Time Series With H Steps
fix.test

The Test of Stability for Auto-Regressive (AR) Approximations With Fixed Parameters
bs.gene

Generate Basis
fix.plot

Plot Results of Estimating
sie.auto.fit

Estimate the Coefficients of Auto-Regressive (AR) Model Automatically
bs.plot

Plots of Basis
fix.pacf.test

Testing Lag of Auto-Regressive (AR) Model
fix.fit

Estimate the Coefficients of Auto-Regressive (AR) Model by User Specifying
fix.pacf

Generate Partial Autocorrelation Function (PACF) by User Specifying
auto.test

The Test of Stability for Auto-Regressive (AR) Approximations Automatically
auto.pacf.test

The Test of Lag of Auto-Regressive (AR) Model Automatically
sie.auto.pacf

Generate Partial Autocorrelation Function (PACF) Automatically
sie.auto.plot

Plot the Estimate Results by Automatic Fitting