dc.contributor.author | Misztal, Małgorzata | |
dc.date.accessioned | 2013-06-04T17:03:00Z | |
dc.date.available | 2013-06-04T17:03:00Z | |
dc.date.issued | 2012 | |
dc.identifier.issn | 0208-6018 | |
dc.identifier.uri | http://hdl.handle.net/11089/1893 | |
dc.description.abstract | Missing data are quite common in practical applications of statistical methods. Imputation
is general statistical method for the analysis of incomplete data sets.
The goal of the paper is to review selected imputation techniques. Special attention is paid to
methods implemented in some packages working in the R environment. An example is presented
to show how to handle missing values using a few procedures of single and multiple imputation
implemented in R. | pl_PL |
dc.language.iso | en | pl_PL |
dc.publisher | Wydawnictwo Uniwersytetu Łódzkiego | pl_PL |
dc.relation.ispartofseries | Acta Universitatis Lodziensis, Folia Oeconomica;269 | |
dc.subject | missing values | pl_PL |
dc.subject | single imputation | pl_PL |
dc.subject | single imputation | pl_PL |
dc.subject | R – project | pl_PL |
dc.title | Imputation of Missing Data Using R Package | pl_PL |
dc.title.alternative | Imputacja brakujących danych z wykorzystaniem środowiska R | pl_PL |
dc.type | Article | pl_PL |
dc.page.number | 131-144 | |
dc.contributor.authorAffiliation | Uniwersytet Łódzki; Wydział Ekonomiczno-Socjologiczny; Instytut Statystyki i Demografii | |