Skip to content
Publish & Distribute
Publishing Solutions
Distribution Solutions
Library Services
Subjects
Architecture and Design
Arts
Business and Economics
Chemistry
Classical and Ancient Near Eastern Studies
Computer Sciences
Cultural Studies
Engineering
General Interest
Geosciences
History
Industrial Chemistry
Jewish Studies
Law
Library and Information Science, Book Studies
Life Sciences
Linguistics and Semiotics
Literary Studies
Materials Sciences
Mathematics
Medicine
Music
Pharmacy
Philosophy
Physics
Social Sciences
Sports and Recreation
Theology and Religion
Publications
Journals
Books
Proceedings
Publishers
Journal Matcher
Blog
Contact
Search
English
English
Deutsch
Polski
Español
Français
Italiano
Cart
Home
Journals
Measurement Science Review
Volume 20 (2020): Issue 1 (February 2020)
Open Access
On Robust Estimation of Error Variance in (Highly) Robust Regression
Jan Kalina
Jan Kalina
The Czech Academy of Sciences, Institute of Computer Science
Praha 8,
The Czech Academy of Sciences, Institute of Information Theory and Automation
Praha 8,
Search for this author on
Sciendo
|
Google Scholar
Kalina, Jan
and
Jan Tichavský
Jan Tichavský
The Czech Academy of Sciences, Institute of Computer Science
Praha 8,
Search for this author on
Sciendo
|
Google Scholar
Tichavský, Jan
Feb 24, 2020
Measurement Science Review
Volume 20 (2020): Issue 1 (February 2020)
About this article
Previous Article
Next Article
Abstract
References
Authors
Articles in this Issue
Preview
PDF
Cite
Share
Download Cover
Published Online:
Feb 24, 2020
Page range:
6 - 14
Received:
Sep 10, 2019
Accepted:
Jan 25, 2020
DOI:
https://doi.org/10.2478/msr-2020-0002
Keywords
High robustness
,
robust regression
,
outliers
,
variance of errors
,
least weighted squares
,
simulation
© 2020 Jan Kalina et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
