print.boot_RRi_fit

Displays a concise summary of the bootstrap RRi model parameter estimates.
The printed output shows the number of bootstrap replicates and a preview
of the parameter estimates from the first few replicates.

Automated and robust framework for analyzing R-R interval (RRi) signals using advanced nonlinear modeling and preprocessing techniques. The package implements a dual-logistic model to capture the rapid drop and subsequent recovery of RRi during exercise, as described by Castillo-Aguilar et al. (2025) <doi:10.1038/s41598-025-93654-6>. In addition, 'CardioCurveR' includes tools for filtering RRi signals using zero-phase Butterworth low-pass filtering and for cleaning ectopic beats via adaptive outlier replacement using local regression and robust statistics. These integrated methods preserve the dynamic features of RRi signals and facilitate accurate cardiovascular monitoring and clinical research.

Matías Castillo-Aguilar

CardioCurveR

Nonlinear Modeling of R-R Interval Dynamics

print.boot_RRi_fit function

<dl><dt>x</dt>
<dd>An object of class "boot_RRi_fit".</dd>
<dt>...</dt>
<dd>Additional arguments passed to <code>print</code>.</dd></dl>

Arguments

Print method for boot_RRi_fit objects — print.boot_RRi_fit

<dl>

<dt>x</dt>
<dd>An object of class "boot_RRi_fit".</dd>


<dt>...</dt>
<dd>Additional arguments passed to <code>print</code>.</dd>

</dl>

print.boot_RRi_fit: Print method for boot_RRi_fit objects

Description

Usage

Value

Arguments