ActCR: ActCosinor_long – R documentation

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ActCosinor_long

Cosinor Model for Circadian Rhythmicity for the Whole Dataset

Description

A parametric approach to study circadian rhythmicity assuming cosinor shape.This function is a whole dataset wrapper for ActCosinor.

Usage

ActCosinor_long(count.data, window = 1)

Arguments

`count.data`	`data.frame` of dimension n * (p+2) containing the p dimensional activity data for all n subject days. The first two columns have to be ID and Day. ID can be either `character` or `numeric`. Day has to be `numeric` indicating the sequence of days within each subject.
`window`	The calculation needs the window size of the data. E.g window = 1 means each epoch is in one-minute window.

Value

A data.frame with the following 5 columns

`ID`	ID
`ndays`	number of days
`mes`	MESRO, which is short for midline statistics of rhythm, which is a rhythm adjusted mean. This represents mean activity level.
`amp`	amplitude, a measure of half the extend of predictable variation within a cycle. This represents the highest activity one can achieve.
`acro`	acrophase, a meaure of the time of the overall high values recurring in each cycle. Here it has a unit of radian. This represents time to reach the peak.
`acrotime`	acrophase in the unit of the time (hours)
`ndays`	Number of days modeled

Examples

counts_1 = example_activity_data$count
cos_all_1 = ActCosinor_long(count.data = counts_1, window = 1)
counts_10 = cbind(counts_1[,1:2],
as.data.frame(t(apply(counts_1[,-c(1:2)], 1,
FUN = bin_data, window = 10, method = "average"))))
cos_all_10 = ActCosinor_long(count.data = counts_10, window = 10)

ActCR

Extract Circadian Rhythms Metrics from Actigraphy Data

v0.2.0

GPL-3

Authors

Junrui Di [aut, cre], Vadim zipunnikov [aut]

Initial release