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Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
trackeR: Infrastructure for Running and Cycling Data from GPS-Enabled Tracking Devices in R | Frick | Journal of Statistical Software
Authors: Hannah Frick, Ioannis Kosmidis
Title: trackeR: Infrastructure for Running and Cycling Data from GPS-Enabled Tracking Devices in R
Abstract: The use of GPS-enabled tracking devices and heart rate monitors is becoming increasingly common in sports and fitness activities. The trackeR package aims to fill the gap between the routine collection of data from such devices and their analyses in R. The package provides methods to import tracking data into data structures which preserve units of measurement and are organized in sessions. The package implements core infrastructure for relevant summaries and visualizations, as well as support for handling units of measurement. There are also methods for relevant analytic tools such as time spent in zones, work capacity above critical power (known as W 0 ), and distribution and concentration profiles. A case study illustrates how the latter can be used to summarize the information from training sessions and use it in more advanced statistical analyses.

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Paper: trackeR: Infrastructure for Running and Cycling Data from GPS-Enabled Tracking Devices in R     Download PDF (Downloads: 621)
Supplements:
trackeR_1.0.0.tar.gz: R source package Download (Downloads: 48; 3MB)
v82i07.R: R replication code Download (Downloads: 71; 5KB)

DOI: 10.18637/jss.v082.i07

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.