We introduced least absolute shrinkage and selection operator ( lasso ) in obtaining periodic signals in unevenly spaced time-series data .
A very simple formulation with a combination of a large set of sine and cosine functions has been shown to yield a very robust estimate , and the peaks in the resultant power spectra were very sharp .
We studied the response of lasso to low signal-to-noise data , asymmetric signals and very closely separated multiple signals .
When the length of the observation is sufficiently long , all of them were not serious obstacles to lasso .
We analyzed the 100-year visual observations of \delta Cep , and obtained a very accurate period of 5.366326 ( 16 ) d. The error in period estimation was several times smaller than in Phase Dispersion Minimization .
We also modeled the historical data of R Sct , and obtained a reasonable fit to the data .
The model , however , lost its predictive ability after the end of the interval used for modeling , which is probably a result of chaotic nature of the pulsations of this star .
We also provide a sample R code for making this analysis .