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Author
Dehnel Grażyna (Poznań University of Economics, Poland)
Title
Robust Regression in Monthly Business Survey
Source
Statistics in Transition, 2015, vol. 16, nr 1, s. 137-152, rys., tab., bibliogr. s. 151-152
Keyword
Odporne metody statystyczne, Statystyka, Obserwacje nietypowe
Robust statistical methods, Statistics, Outliers
Note
summ., Materiały z konferencji Multivariate Statistical Analysis 2014, Łódź.
Abstract
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. (original abstract)
Accessibility
The Main Library of the Cracow University of Economics
The Library of University of Economics in Katowice
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Bibliography
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ISSN
1234-7655
Language
eng
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