We discuss time-series analyses of classical Cepheid and RR Lyrae variables in the Galaxy and the Magellanic Clouds at multiple wavelengths. We adopt the Fourier decomposition method to quantify the structural changes in the light curves of Cepheid and RR Lyrae variables. A quantitative comparison of Cepheid Fourier parameters suggests that the canonical mass-luminosity models that lie towards the red-edge of the instability strip show a greater offset with respect to observations for short-period Cepheids. RR Lyrae models are consistent with observations in most period bins. We use ensemble light curve analysis to predict the physical parameters of observed Cepheid and RR Lyrae variables using machine learning methods. Our preliminary results suggest that the posterior distributions of mass, luminosity, temperature and radius for Cepheids and RR Lyraes can be well-constrained for a given metal abundance, provided a smoother grid of models is adopted in various input physical parameters.
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