Description Usage Arguments Value References See Also Examples
In a group of individuals with physcial activity data, this function utilize Fast Fourier Transform (FFT) and L1/L2 penalties to select significant harmonics/periodicities and describe the main activity pattern (circadian rhythm) among the population.
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df 
the tbl_df data frame containing at least two variables: subject ID and activity. The function 
Nlength 
the length of observations necessary for each individual, note that it should be consistent among all 
Nlambda 
λ's take values from 0 to 2max(X_k^2), as 0 gives no penalty and the latter suppresses all θ's to 0. Therefore, we divide 2max(X_k^2) into Nlambda (default to be 100) λ's to pick frequencies/harmonics/periodicities. 
alpha 
the tuning parameter controlling the balance between L1 and L2 penalty. The default is 1, using complete Lasso/ L1 penalty. 
Ntop 
the number of frequencies/harmonics/periodicities picked for the population. The default is 5. 
cross 
whether to perform crossvalidation. The default is FALSE. 
Ncross 
the number of groups of data for crossvalidation. If cross=TRUE, the data shall be divided into Ncross groups. 
plot 
whether to plot: MSE against the number of nonzero θ's, and only the points at which the number of nonzero θ's changes (as λ changes) are be plotted. The default is TRUE. 
if no crossvalidation is conducted, return a list; if crossvalidation, return a list of lists, with the last list consisting of all FFT results and crossvalidation groups (showing the subject IDs leaveout /NOT used each time).
topfreq 
vector of length 
mse 
vector of length 
nonzero 
vector of length 
deltazero 
vector of length 
lambda 
vector of length 
theta 

xscore 

xprop 

freq 
vector of length 
Li, X. , Kane, M. , Zhang, Y. , Sun, W. , Song, Y. , Dong, S. , Lin, Q. , Zhu, Q. , Jiang, F. & Zhao, H. (2019). Penalized Selection of Periodicities Characterizes the Consolidation of SleepWake Circadian Rhythms During Early Childhood Development. Submitted.
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