print.fastcpd

print,fastcpd-method

Print the call and the change points for a fastcpd object

Implements fast change point detection algorithm based on the
paper "Sequential Gradient Descent and Quasi-Newton's Method for
Change-Point Analysis" by Xianyang Zhang, Trisha Dawn
<https://proceedings.mlr.press/v206/zhang23b.html>. The algorithm is
based on dynamic programming with pruning and sequential gradient
descent. It is able to detect change points a magnitude faster than
the vanilla Pruned Exact Linear Time(PELT). The package includes
examples of linear regression, logistic regression, Poisson
regression, penalized linear regression data, and whole lot more
examples with custom cost function in case the user wants to use their
own cost function.

Xingchi Li

fastcpd

Fast Change Point Detection via Sequential Gradient Descent

Xianyang Zhang

print.fastcpd function

<dl><dt>x</dt>
<dd>A fastcpd object.</dd>
<dt>...</dt>
<dd>Ignored.</dd></dl>

Arguments

Print the call and the change points for a fastcpd object — print.fastcpd

<dl>

<dt>x</dt>
<dd>A fastcpd object.</dd>


<dt>...</dt>
<dd>Ignored.</dd>

</dl>

print.fastcpd: Print the call and the change points for a fastcpd object

Description

Usage

Value

Arguments