GGIR (version 3.2-0)

g.fragmentation: Fragmentation metrics from time series.

Description

The function is used by g.part5 to derive time series fragmentation metrics. The function assumes that NA values and nonwear time is accounted for before the data enters the function.

Usage

g.fragmentation(frag.metrics = c("mean", "TP", "Gini", "power",
        "CoV", "NFragPM", "all"), LEVELS = c(), Lnames=c(), xmin=1, mode = "day")

Value

List with Character object showing how decimals are separated

TP_PA2IN

Transition probability physical activity to inactivity

.

TP_IN2PA

Transition probability physical inactivity to activity

Nfrag_IN2LIPA

Number of inacitivty fragments succeeded by LIPA (light physical activity)

TP_IN2LIPA

Transition probability physical inactivity to LIPA

Nfrag_IN2MVPA

Number of inacitivty fragments succeeded by MVPA (moderate or vigorous physical activity)

TP_IN2MVPA

Transition probability physical inactivity to MVPA

Nfrag_MVPA

Number of MVPA fragments

Nfrag_LIPA

Number of LIPA fragments

mean_dur_MVPA

mean MVPA fragment duration

mean_dur_LIPA

mean LIPA fragment duration

Nfrag_IN

Number of inactivity fragments

Nfrag_PA

Number of activity fragments

mean_dur_IN

mean duration inactivity fragments

mean_dur_PA

mean duration activity fragments

Gini_dur_IN

Gini index corresponding to inactivity fragment durations

Gini_dur_PA

Gini index corresponding to activity fragment durations

CoV_dur_IN

Coefficient of Variance corresponding to inactivity fragment durations

CoV_dur_PA

Coefficient of Variance corresponding to activity fragment durations

alpha_dur_IN

Alpha of the fitted power distribution through inactivity fragment durations

alpha_dur_PA

Alpha of the fitted power distribution through activity fragment durations

x0.5_dur_IN

x0.5 corresponding to alpha_dur_IN

x0.5_dur_PA

x0.5 corresponding to alpha_dur_PA

W0.5_dur_IN

W0.5 corresponding to alpha_dur_IN

W0.5_dur_PA

W0.5 corresponding to alpha_dur_PA

NFragPM_IN

Number of IN fragments per minutes in IN

NFragPM_PA

Number of PA fragments per minutes in PA

SD_dur_IN

Standard deviation in the duration of inactivity fragments

SD_dur_PA

Standard deviation in the duration of physical activity fragments

Arguments

frag.metrics

Character with fragmentation metric to exract. Can be "mean", "TP", "Gini", "power", or "CoV", "NFragPM", or all the above metrics with "all". See details.

LEVELS

Numeric vector of behavioural level classes derived with identify_levels

Lnames

Character vector with names of classes used in LEVELS, see details.

xmin

Numeric scalar to indicate the minimum recordable fragment length. In g.part5 this is derived from the epoch length.

mode

Character to indicate whether input data is daytime ("day") or sleep period time ("spt").

Author

Vincent T van Hees <[e-mail]>

Details

See package vignette for description of fragmentation metrics. In short, abbreviation "TP" refers to transition probality metrics, abbreviation "CoV" refers to Coefficient of Variance, and metric "NFragPM" refers to the Number of fragments per minute.

Regarding the Lnames argument. The class names included in this are categorised as follows:

• Inactive, if name includes the character strings "day_IN_unbt" or "day_IN_bts"

• LIPA, if name includes the character strings "day_LIG_unbt" or "day_LIG_bts"

• MVPA, if name includes the character strings "day_MOD_unbt", "day_VIG_unbt", or "day_MVPA_bts"

Examples

if (FALSE) {
    x = c(6, 5, 6, 7, 6, 6, 7, 6, 6, 5, 6, 6, 6, 5, 7, 6, 6, 5, 5, 5, 6, 7, 6,
        6, 6, 6, 7, 6, 5, 5, 5, 5, 5, 6, 6, 6, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6,
        7, 7, 6, 5, 6, 5, 6, 5, rep(12, 11), 5, 6, 6, 6, 5, 6, rep(9, 14), 6,
        5, 7, 7, 6, 7, 7, 7, 6, 6, 6, 5, 6, 5, 5, 5, 6, 5, 5, 5, 5, 5, 5, 5)
  Lnames = c("spt_sleep", "spt_wake_IN", "spt_wake_LIG", "spt_wake_MOD",
            "spt_wake_VIG", "day_IN_unbt", "day_LIG_unbt", "day_MOD_unbt",
            "day_VIG_unbt", "day_MVPA_bts_10", "day_IN_bts_30",
             "day_IN_bts_10_30", "day_LIG_bts_10")
  out = g.fragmentation(frag.metrics = "all",
                        LEVELS = x,
                        Lnames=Lnames)}