Perovic, G. (2022) Robust PEROBLS 3 Method of Least Squares. In: Research Developments in Science and Technology Vol. 5. B P International, pp. 114-126. ISBN 978-93-5547-671-5
Full text not available from this repository.Abstract
Outliers, or result with gross errors, are, practically, always present in regression models. Therefore, it is very important to study the regression with influence of outliers as low as possible. So, dealing with this problem I have studied a new robust Least Square (LS) Method, named after the author PEROBLS and based on the real stochastical model. Namely, the variance of an observation which has a gross error is substituted by its mean square error composed of random and gross observation error. The gross error is exactly and unbiasedly estimated in the LS model and therefore there exists only one or two adjustment iteration.
Item Type: | Book Section |
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Subjects: | Science Global Plos > Multidisciplinary |
Depositing User: | Unnamed user with email support@science.globalplos.com |
Date Deposited: | 13 Oct 2023 04:20 |
Last Modified: | 13 Oct 2023 04:20 |
URI: | http://ebooks.manu2sent.com/id/eprint/1705 |