Statistical modeling based on multiple time series with various time resolution

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In this research project, we developed a method of statistical modeling to work with multiple time series observed with various resolutions or different observation intervals. Especially, we are interested in some interpolation method making use of the inter-relationship between the time series with different observation frequencies. In application, we focused on the de-convolution of annual time series(the final estimate of GDP for example) with the help of closely related quarterly time series(the quick estimates of quarterly GDP for example).