Robust regression in monthly business survey

Grażyna Dehnel


There are many sample surveys of populations that contain outliers (extreme values). This is especially true in business, agricultural, household and medicine surveys. Outliers can have a large distorting influence on classical statistical methods that are optimal under the assumption of normality or linearity. As a result, the presence of extreme observations may adversely affect estimation, especially when it is carried out at a low level of aggregation. To deal with this problem, several alternative techniques of estimation, less sensitive to outliers, have been proposed in the statistical literature. In this paper we attempt to apply and assess some robust regression methods (LTS, M-estimation, S-estimation, MM-estimation) in the business survey conducted within the framework of official statistics.
Author Grażyna Dehnel (WIiGE / KS)
Grażyna Dehnel,,
- Department of Statistics
Journal seriesStatistics in Transition, ISSN 1234-7655, e-ISSN 2450-0291, (B 15 pkt)
Issue year2015
Publication size in sheets0.75
Keywords in Polishregresja odporna, detekcja obserwacji odstających, statystyka przedsiębiorstw
Keywords in Englishrobust regression, outlier detection, business statistics
ASJC Classification1804 Statistics, Probability and Uncertainty; 2613 Statistics and Probability
Languageen angielski
Score (nominal)15
Score sourcejournalList
ScoreMinisterial score = 15.0, 19-12-2019, ArticleFromJournal
Ministerial score (2013-2016) = 15.0, 19-12-2019, ArticleFromJournal
Publication indicators Scopus SNIP (Source Normalised Impact per Paper): 2016 = 0.26
Citation count*6 (2020-09-12)
Share Share

Get link to the record

* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
Are you sure?