bfa_boot1_ls

This function performs single bootstrapping of the least squares estimators
of the autoregressive coefficients in a bifurcating autoregressive (BAR)
model of any order <code>p</code> as described in Elbayoumi and Mostafa (2020).

Estimation of bifurcating autoregressive models of any order, p, BAR(p) as well as several types of bias correction for the least squares estimators of the autoregressive parameters as described in Zhou and Basawa (2005) <doi:10.1016/j.spl.2005.04.024> and Elbayoumi and Mostafa (2020) <doi:10.1002/sta4.342>. Currently, the bias correction methods supported include bootstrap (single, double and fast-double) bias correction and linear-bias-function-based bias correction. Functions for generating and plotting bifurcating autoregressive data from any BAR(p) model are also included. This new version includes calculating several type of bias-corrected and -uncorrected confidence intervals for the least squares estimators of the autoregressive parameters as described in Elbayoumi and Mostafa (2023)
<doi:10.6339/23-JDS1092>.

Tamer Elbayoumi

bifurcatingr

Bifurcating Autoregressive Models

Sayed Mostafa

bfa_boot1_ls function

<dl><dt>z</dt>
<dd>a numeric vector containing the tree data</dd>
<dt>p</dt>
<dd>an integer determining the order of bifurcating autoregressive model
to be fit to the data</dd>
<dt>burn</dt>
<dd>number of tree generations to discard before starting the
bootstrap sample (replicate)</dd>
<dt>B</dt>
<dd>number of bootstrap samples (replicates)</dd>
<dt>boot_est</dt>
<dd>a logical that determines whether the bootstrapped least
squares estimates of the autoregressive coefficients should be returned.
Defaults to TRUE.</dd>
<dt>boot_data</dt>
<dd>a logical that determines whether the bootstrap samples
should be returned. Defaults to FALSE.</dd></dl>

Arguments

Single Bootstrap of Least Squares Estimators of BAR(p) Models — bfa_boot1_ls

<dl>

<dt>z</dt>
<dd>a numeric vector containing the tree data</dd>


<dt>p</dt>
<dd>an integer determining the order of bifurcating autoregressive model
to be fit to the data</dd>


<dt>burn</dt>
<dd>number of tree generations to discard before starting the
bootstrap sample (replicate)</dd>


<dt>B</dt>
<dd>number of bootstrap samples (replicates)</dd>


<dt>boot_est</dt>
<dd>a logical that determines whether the bootstrapped least
squares estimates of the autoregressive coefficients should be returned.
Defaults to TRUE.</dd>


<dt>boot_data</dt>
<dd>a logical that determines whether the bootstrap samples
should be returned. Defaults to FALSE.</dd>

</dl>

bfa_boot1_ls: Single Bootstrap of Least Squares Estimators of BAR(p) Models

Description

Usage

Value

Arguments

References

Examples