get_cvPER: Calculate coefficient of variation in sliding windows

Description Usage Arguments Value Examples

View source: R/IMU_ActiGraph_Scripts.R

Description

Calculates coefficient of variation using the approach of Crouter et al. (2010, Med Sci Sports Exerc)

Usage

1
get_cvPER(big_data, window_secs = 10, Algorithm, verbose = FALSE)

Arguments

big_data

a numeric vector on which to perform the calculation

window_secs

size of the sliding window, in seconds

Algorithm

A numeric vector giving the algorithm(s) to apply to the data from the primary accelerometer and (if applicable) IMU

verbose

A logical scalar: print progress updates?

Value

a numeric vector of values, giving the lowest coefficient of variation among the sliding windows that correspond to each epoch of data

Examples

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data(raw_for_cv)
get_cvPER(raw_for_cv$ENMO, Algorithm = 1)

TwoRegression documentation built on May 2, 2019, 6:33 a.m.