Handling Compositional Time Series with Varying Number of Parts
(2018) CoDaWork 2017 In Austrian Journal of Statistics 47(5). p.26-33- 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.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/9004462b-e009-4fce-8942-fe059b4bb2ee
- author
- Bergman, Jakob
LU
- organization
- publishing date
- 2018-09-26
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- compositional loess, compositional time series, imputation, political party preference polls, polls Sweden
- in
- Austrian Journal of Statistics
- volume
- 47
- issue
- 5
- pages
- 26 - 33
- publisher
- Austrian Society for Statistics
- conference name
- CoDaWork 2017
- conference location
- Abbadia San Salvatore, Siena, Italy
- conference dates
- 2017-06-05 - 2017-06-09
- external identifiers
-
- scopus:85063482942
- ISSN
- 1026-597X
- DOI
- 10.17713/ajs.v47i5.738
- language
- English
- LU publication?
- yes
- id
- 9004462b-e009-4fce-8942-fe059b4bb2ee
- date added to LUP
- 2018-06-25 11:45:57
- date last changed
- 2024-03-13 15:59:49
@article{9004462b-e009-4fce-8942-fe059b4bb2ee, 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 = {{Bergman, Jakob}}, issn = {{1026-597X}}, keywords = {{compositional loess; compositional time series; imputation; political party preference polls; polls Sweden}}, language = {{eng}}, month = {{09}}, number = {{5}}, pages = {{26--33}}, publisher = {{Austrian Society for Statistics}}, series = {{Austrian Journal of Statistics}}, title = {{Handling Compositional Time Series with Varying Number of Parts}}, url = {{https://lup.lub.lu.se/search/files/51836842/738_Article_Text_2928_1_10_20180826.pdf}}, doi = {{10.17713/ajs.v47i5.738}}, volume = {{47}}, year = {{2018}}, }