Exploring incomplete data using visualization techniques
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DOI: 10.1007/s11634-011-0102-y
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Cited by:
- Juana Sanchez & Sydney Noelle Kahmann, 2017. "R&D, Attrition and Multiple Imputation in BRDIS," Working Papers 17-13, Center for Economic Studies, U.S. Census Bureau.
- Kowarik, Alexander & Templ, Matthias, 2016. "Imputation with the R Package VIM," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 74(i07).
- Elena Catanese, 2016. "Data Editing for Complex Surveys in Presence Of Administrative Data: An Application to Fss 2013 Livestock Survey Data Based on The Joint Sequential Use Of Different R Packages," Romanian Statistical Review, Romanian Statistical Review, vol. 64(2), pages 101-117, June.
- M. Templ & K. Hron & P. Filzmoser, 2017. "Exploratory tools for outlier detection in compositional data with structural zeros," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(4), pages 734-752, March.
- Alfons, Andreas & Templ, Matthias, 2013. "Estimation of Social Exclusion Indicators from Complex Surveys: The R Package laeken," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 54(i15).
- Matthias Templ & Alexander Kowarik & Bernhard Meindl, 2014. "Development and Current Practice in Using R at Statistics Austria," Romanian Statistical Review, Romanian Statistical Review, vol. 62(2), pages 173-184, June.
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More about this item
Keywords
Visualization; Missing values; Exploring incomplete data; $${{sf R}}$$ software; 62-XX Statistics; 00A66 Mathematics and visual arts; visualization;All these keywords.
JEL classification:
Statistics
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