ActCosinor2             Cosinor Model for Circadian Rhythmicity
ActCosinor_long2        Cosinor Model for Circadian Rhythmicity for the
                        Whole Dataset
ActExtendCosinor2       Extended Cosinor Model for Circadian
                        Rhythmicity
ActExtendCosinor_long2
                        Cosinor Model for Circadian Rhythmicity for the
                        Whole Dataset
DataShrink              Annotating the merged data for all
                        accelerometer files in the GGIR output
IS2                     Interdaily Statbility
IS_long2                Interdaily Statbility for the Whole Dataset
IV2                     Intradaily Variability
IV_long2                Intradaily Variability for the Whole Dataset
NormalizeGGIRDate       Normalize GGIR dates to ISO format
PAfun                   Timne Metrics for Whole Dataset
RA2                     Relative Amplitude
RA_long2                Relative Amplitude for the Whole Datset
SVDmiss2                Modified SVDmiss function (package
                        SpatioTemporal)
Time2                   Time of A Certain activity State
Time_long2              Timne Metrics for Whole Dataset
Tvol2                   Total Volumen of Activity for Whole Dataset
bin_data2               Bin data into longer windows
create.shell            Create a template shell script of mMARCH.AC
data.imputation         Data imputation for the cleaned data with
                        annotation
fragmentation2          Fragmentation Metrics
fragmentation_long2     Fragmentation Metrics for Whole Dataset
get_mean_sd_hour        get subject average of time variables
ggir.datatransform      Transform the data and merge all accelerometer
                        files in the GGIR output
ggir.summary            Description of all accelerometer files in the
                        GGIR output
jive.predict2           Modified jive.predict function (package:
                        r.jive)
mMARCH.AC.maincall      Main Call for Data Processing after Runing GGIR
                        for Accelerometer Data
makeSleepDataMatrix     Make a sleep matrix based on the sleep onset
                        and wake up time
pheno.plot              View phenotype variables
wear_flag               Create Wear/Nonwear Flags
