Handling Compositional Time Series with Varying Number of Parts

Authors

DOI:

https://doi.org/10.17713/ajs.v47i5.738

Abstract

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.

Author Biography

Jakob Bergman, Lund University

Department of Statistics, Senior lecturer

Published

2018-09-08

How to Cite

Bergman, J. (2018). Handling Compositional Time Series with Varying Number of Parts. Austrian Journal of Statistics, 47(5), 26-33. https://doi.org/10.17713/ajs.v47i5.738

Issue

Section

CoDaWork 2017