Handling Compositional Time Series with Varying Number of Parts
Jakob Bergman · Austrian Journal of Statistics · 2018
When different polling organisations conduct political party preference polls at different times, different parties might be reported. If the estimated voter shares of these polls are combined into a time series we obtain a compositional time series, but with varying number of parts, thus prohibiting the use of standard compositional time series analysis tools. We discuss the problem and suggest a solution by imputing the unreported parts. The method is applied to a short compositional time series of party preference polls from Sweden.