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Title | Detecting bivariate outliers on the basis of normalizing transformations for non-Gaussian data |
Authors |
Prykhodko, S.
Prykhodko, N. Makarova, L. Kudin, O. Smykodub, T. Prykhodko, A. |
ORCID | |
Keywords |
outlier normalizing transformation bivariate non-Gaussian data Mahalanobis squared distance F distribution prediction ellipse |
Type | Conference Papers |
Date of Issue | 2017 |
URI | http://essuir.sumdu.edu.ua/handle/123456789/55754 |
Publisher | Sumy State University |
License | Copyright not evaluated |
Citation | Detecting bivariate outliers on the basis of normalizing transformations for non-Gaussian data [Текст] / S. Prykhodko, N. Prykhodko, L. Makarova [et al.] // Advanced Information Systems and Technologies : proceedings of the V international scientific conference, Sumy, May 17-19 2017/ Edited by S.І. Protsenko, V.V. Shendryk. - Sumy : Sumy State University, 2017. - P. 95-97. |
Abstract |
The statistical technique for detecting
outliers in bivariate non-Gaussian data on the basis of
normalizing transformations, prediction ellipse and a
test statistic (TS) for the Mahalanobis squared
distance (MSD), which has an approximate F
distribution, is proposed. Application of the technique
is considered for detecting outliers in two bivariate
non-Gaussian data sets: the first, actual effort (hours)
and size (adjusted function points) from 145
maintenance and development projects, the second,
effort (hours) and mass (tonnes) of designed the
section of the ship from 188 designs of sections. |
Appears in Collections: |
Наукові видання (ЕлІТ) |
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File | Size | Format | Downloads |
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Prykhodko_Data.pdf | 748.84 kB | Adobe PDF | 1667061002 |
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