Simulated Accelerometer Data for Clustering

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Abstract/Contents

Abstract

The data provided correspond to an extensive simulation study to evaluate methods for applying prediction strength when the interest lies in identifying clusters based on accelerometer time series. The study contains simulated accelerometer data generated under 28 different scenarios according to procedures outlined in Yu et. al. 2023.

This repository contains 28 zip files. Each zip file corresponds to a different set of data generation parameters (scenarios) and contains 100 simulated data sets per scenario. Each data set is in RDS format.

Additional materials include an Excel spreadsheet (data info.xlsx) containing relevant data generation parameters for each scenario and a data dictionary for the simulated data sets. Included also is a sample R script (exampleCode.R) which can be used to load a data set, visualize its contents, and apply the prediction.strength and pam algorithms.

We are providing the data used in Yu et al along with code for full transparency and to facilitate others who wish to use the methods described in the paper.

Questions may be directed to Kristopher Kapphahn (kikapp@stanford.edu).

Description

Type of resource Dataset, text
Date created [ca. February 2023]
Date modified February 10, 2023; February 10, 2023; February 21, 2023; February 27, 2023
Publication date February 8, 2023

Creators/Contributors

Author Yu, Kevin
Author Kapphahn, Kristopher
Author Moore IV, Hyatt
Author Haydel, Farish
Author Robinson, Thomas
Author Desai, Manisha

Subjects

Subject Cluster analysis
Subject Accelerometer
Subject Prediction Strength
Subject Physical Activity
Genre Data
Genre Tabular data
Genre Data sets
Genre Dataset
Genre Tables (data)

Bibliographic information

Access conditions

Use and reproduction
User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
License
This work is licensed under a Creative Commons Attribution Non Commercial Share Alike 4.0 International license (CC BY-NC-SA).

Preferred citation

Preferred citation
Yu, K., Kapphahn, K., Moore IV, H., Haydel, F., Robinson, T., and Desai, M. (2023). Simulated Accelerometer Data for Clustering. Stanford Digital Repository. Available at https://purl.stanford.edu/cg185zq8485. https://doi.org/10.25740/cg185zq8485.

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