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TwoRegression (version 1.1.1)

Develop and Apply Two-Regression Algorithms

Description

Facilitates development and application of two-regression algorithms for research-grade wearable devices. It provides an easy way for users to access previously-developed algorithms, and also to develop their own. Initial motivation came from Hibbing PR, LaMunion SR, Kaplan AS, & Crouter SE (2018) . However, other algorithms are now supported. Please see the associated references in the package documentation for full details of the algorithms that are supported.

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Version

Install

install.packages('TwoRegression')

Monthly Downloads

137

Version

1.1.1

License

GPL-3

Issues

Pull Requests

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Repository

https://github.com/paulhibbing/TwoRegression

Maintainer

Paul Hibbins

Last Published

November 19th, 2025

Functions in TwoRegression (1.1.1)

raw_to_collapse

Primary accelerometer data to collapse

imu_to_collapse

IMU data to collapse

Smooth two-regression estimates over specified periods

hibbing-helpers

Apply a Hibbing 2018 two-regression algorithm

plot.TwoRegression

Create summary plots for TwoRegression objects

Convert a linear model to a text representation of the prediction equation

summary.TwoRegression

Summary method for TwoRegression objects

Develop a cut-point as part of the process for developing a two-regression algorithm

Develop a two-regression algorithm

TwoRegression-Package

Develop and Apply Two-Regression Algorithms

predict.TwoRegression

Predict metabolic equivalents from a TwoRegression object

Calculate direction changes per five seconds in sliding windows

Activity count data for demonstrating prior two-regression models

TwoRegression-Function

Apply an existing two-regression model

Perform leave-one-participant-out-cross-validation on a two-regression algorithm

Plot behaviors for visualizing a walk/run cut-point

Coefficient of variation for two-regression models

Two-regression-ready data frame

Add a cut-point to a plot

Plot behaviors for visualizing a sedentary cut-point

get_2rm_formula

Convert an object of class TwoRegression to a textual representation of the algorithm

Primary accelerometer data to calculate coefficient of variation per 10-s

hibbing-input-validation

Internal functions for the 2RM wrapper

IMU data to check