Sector based linear regression, a new robust method for the multiple linear regression
This paper describes a new robust multiple linear regression method, which based on the segmentation of the N dimensional space to N+1 sector. An N dimensional regression plane is located so that the half (or other) part of the points are under this plane in each sector. This article also presents a...
Elmentve itt :
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| Dokumentumtípus: | Cikk |
| Megjelent: |
University of Szeged, Institute of Informatics
Szeged
2018
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| Sorozat: | Acta cybernetica
23 No. 4 |
| Kulcsszavak: | Regresszió - lineáris |
| Tárgyszavak: | |
| doi: | 10.14232/actacyb.23.4.2018.3 |
| Online Access: | http://acta.bibl.u-szeged.hu/58181 |
| Tartalmi kivonat: | This paper describes a new robust multiple linear regression method, which based on the segmentation of the N dimensional space to N+1 sector. An N dimensional regression plane is located so that the half (or other) part of the points are under this plane in each sector. This article also presents a simple algorithm to calculate the parameters of this regression plane. This algorithm is scalable well by the dimension and the count of the points, and capable to calculation with other (not 0.5) quantiles. This paper also contains some studies about the described method, which analyze the result with different datasets and compares to the linear least squares regression. Sector Based Linear Regression (SBLR) is the multidimensional generalization of the mathematical background of a point cloud processing algorithm called Fitting Disc method, which has been already used in practice to process LiDAR data. A robust regression method can be used also in many other fields. |
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| Terjedelem/Fizikai jellemzők: | 1017-1038 |
| ISSN: | 0324-721X |