F_test_cfar

F test for a CFAR process to specify the CFAR order.

Simulation, estimation, prediction procedure, and model identification methods for nonlinear time series analysis, including threshold autoregressive models, Markov-switching models, convolutional functional autoregressive models, nonlinearity tests, Kalman filters and various sequential Monte Carlo methods. More examples and details about this package can be found in the book "Nonlinear Time Series Analysis" by Ruey S. Tsay and Rong Chen, John Wiley & Sons, 2018 (ISBN: 978-1-119-26407-1).

Xialu Liu

Nonlinear Time Series Analysis

Ruey Tsay

Rong Chen

F_test_cfar function

<dl><dt>f</dt>
<dd>the functional time series.</dd>
<dt>p.max</dt>
<dd>the maximum CFAR order. Default is 6.</dd>
<dt>df_b</dt>
<dd>the degrees of freedom for natural cubic splines. Default is 10.</dd>
<dt>grid</dt>
<dd>the number of gird points used to construct the functional time series and noise process. Default is 1000.</dd></dl>

Arguments

F Test for a CFAR Process — F_test_cfar

<dl>

<dt>f</dt>
<dd>the functional time series.</dd>


<dt>p.max</dt>
<dd>the maximum CFAR order. Default is 6.</dd>


<dt>df_b</dt>
<dd>the degrees of freedom for natural cubic splines. Default is 10.</dd>


<dt>grid</dt>
<dd>the number of gird points used to construct the functional time series and noise process. Default is 1000.</dd>

</dl>

F_test_cfar: F Test for a CFAR Process

Description

Usage

Value

Arguments

References