sie.auto.fit

sie.auto.fit() estimates the coefficients of AR model by sieve methods with 2 cross validation methods and elbow method.

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.

Xiucai Ding

Sie2nts

Sieve Methods for Non-Stationary Time Series

Chen Qian

sie.auto.fit function

<dl><dt>ts</dt>
<dd>ts is the data set which is a time series data typically</dd>
<dt>type</dt>
<dd>type indicates which type of basis is used. There are 31 types in this package</dd>
<dt>or</dt>
<dd>indicates the order of spline and only used in Cspli type, default is 4 which indicates cubic spline</dd>
<dt>method</dt>
<dd>method indicates which method used to choose optimal parameters, 3 methods in this package can be used</dd>
<dt>m</dt>
<dd>m indicates the number of points of coefficients to estimate</dd>
<dt>threshold</dt>
<dd>threshold determines the bound for Elbow method</dd></dl>

Arguments

Estimate the Coefficients of Auto-Regressive (AR) Model Automatically — sie.auto.fit

<dl>

<dt>ts</dt>
<dd>ts is the data set which is a time series data typically</dd>


<dt>type</dt>
<dd>type indicates which type of basis is used. There are 31 types in this package</dd>


<dt>or</dt>
<dd>indicates the order of spline and only used in Cspli type, default is 4 which indicates cubic spline</dd>


<dt>method</dt>
<dd>method indicates which method used to choose optimal parameters, 3 methods in this package can be used</dd>


<dt>m</dt>
<dd>m indicates the number of points of coefficients to estimate</dd>


<dt>threshold</dt>
<dd>threshold determines the bound for Elbow method</dd>

</dl>

sie.auto.fit: Estimate the Coefficients of Auto-Regressive (AR) Model Automatically

Description

Usage

Value

Arguments