Direct solution of polynomial regression of order up to 3

dc.citation.epage42
dc.citation.issue3
dc.citation.journalTitleВимірювальна техніка та метрологія
dc.citation.spage35
dc.citation.volume83
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorDorozhovets, Mykhaylo
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2023-05-09T10:30:46Z
dc.date.available2023-05-09T10:30:46Z
dc.date.created2022-02-28
dc.date.issued2022-02-28
dc.description.abstractThis article presents results related to the direct solution of the polynomial regression parameters based on the analytical solving of regression equations. The analytical solution is based on the normalization of the values of independent quantity with equidistance steps. The proposed solution does not need to directly solve a system of polynomial regression equations. The direct expressions to calculate estimators of regression coefficients, their standard deviations, and also standard and expanded deviation of polynomial functions are given. For a given number of measurement points, the parameters of these expressions have the same values independently of the range of input quantity. The proposed solution is illustrated by a numerical example used from a literature source.
dc.format.extent35-42
dc.format.pages8
dc.identifier.citationDorozhovets M. Direct solution of polynomial regression of order up to 3 / Mykhaylo Dorozhovets // Measuring equipment and metrology. — Lviv : Lviv Politechnic Publishing House, 2022. — Vol 83. — No 3. — P. 35–42.
dc.identifier.citationenDorozhovets M. Direct solution of polynomial regression of order up to 3 / Mykhaylo Dorozhovets // Measuring equipment and metrology. — Lviv : Lviv Politechnic Publishing House, 2022. — Vol 83. — No 3. — P. 35–42.
dc.identifier.doidoi.org/10.23939/istcmtm2022.03.035
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/59071
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofВимірювальна техніка та метрологія, 3 (83), 2022
dc.relation.ispartofMeasuring equipment and metrology, 3 (83), 2022
dc.relation.references[1] M. G. Kendall and A. Stuart (1966) The advanced theory of statistics. Vol. 2. Inference and relationship. Second Edition. Chares Griffin and Company Limited, London. https://archive.org/details/in.ernet.dli.2015.212877.
dc.relation.references[2] Draper, N. and Smith, H. (1981) Applied Regression Analysis. 2nd ed., Wiley, New York. https://onlinelibrary.wiley.com/doi/book/10.1002/9781118625590.
dc.relation.references[3] J. O. Rawlings, S. G. Pantula, D. A. Dickey (1998) Applied Regression Analysis: A Research Tool, Second Edition, Springer-Verlag. New York, Berlin, Heidelberg. https://doi.org/10.1007/b98890.
dc.relation.references[4] Handbook of Applicable Mathematics. Vol. VI: Statistics, Part A, (1984). Edited by Emlyn Lloyd, John Wiley and Sons. https://www.amazon.com/Handbook-Applicable-Mathematics-Statistics-6/dp/0471900249.
dc.relation.references[5] J. H. Pollard. (1977) Handbook of Numerical and Statistical Techniques. Cambridge University Press. https://cc.bingj.com/cache.aspx?q=J.H.+Pollard.+(1977)+Handbook+of+Numerical+and+Statistical+Techniques.d=4579616625657925&mkt=en-WW&setlang=en-US&w=lYKqOOVXlYsikZD-qV7p9HJrRgt2oDA3.
dc.relation.references[6] Applied Linear Regression, 3rd ed. Willey, Hoboken (2005). https://openlibrary.org/books/OL3306403M/Applied_linear_regression.
dc.relation.references[7] J. R. Taylor (1982). An introduction to error analysis. University Science Books Mill Valley, California 1982. https://openlibrary.org/books/OL3786923M/An_introduction_to_error_analysis.
dc.relation.references[8] B. Forbes (2009), Parameter estimation based on leastsquares methods. In F. Pavese and A. B. Forbes, editors, Data modeling for metrology and testing in measurement science, New York. Birkauser-Boston. https://link.springer.com/chapter/10.1007/978-0-8176-4804-6_5.
dc.relation.references[9] G. Mejer (2008), Smart Sensor Systems. John Wiley, 2008. https://onlinelibrary.wiley.com/doi/book/10.1002/9780470866931.
dc.relation.references[10] Evaluation of measurement data – Guide to the expression of uncertainty in measurement Joint Committee for Guides in Metrology, JCGM 100: 2008. https://www.iso.org/sites/JCGM/GUM/JCGM100/.
dc.relation.references[11] JCGM 101:2008. Evaluation of measurement data – Supplement 1 to the ‘Guide to the Expression of Uncertainty in Measurement – propagation of distributions using a Monte Carlo method’. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP and OIML. https://www.bipm.org/documents/20126/2071204/JCGM.
dc.relation.references[12] Dorozhovets M. Study of the effect of correlation of observation results on the uncertainty of linear regression. Pomiary, Automatyka, Kontrola. N12, 2008, s. 31–34 (in Polish). https://bibliotekanauki.pl/issues/8204.
dc.relation.references[13] Dorozhovets M. Include measurement uncertainty of both quantities in linear regression. Pomiary, Automatyka, Kontrola. N9, 2008, pp. 612–615 (in Polish). https://bibliotekanauki.pl/issues/8089.
dc.relation.referencesen[1] M. G. Kendall and A. Stuart (1966) The advanced theory of statistics. Vol. 2. Inference and relationship. Second Edition. Chares Griffin and Company Limited, London. https://archive.org/details/in.ernet.dli.2015.212877.
dc.relation.referencesen[2] Draper, N. and Smith, H. (1981) Applied Regression Analysis. 2nd ed., Wiley, New York. https://onlinelibrary.wiley.com/doi/book/10.1002/9781118625590.
dc.relation.referencesen[3] J. O. Rawlings, S. G. Pantula, D. A. Dickey (1998) Applied Regression Analysis: A Research Tool, Second Edition, Springer-Verlag. New York, Berlin, Heidelberg. https://doi.org/10.1007/b98890.
dc.relation.referencesen[4] Handbook of Applicable Mathematics. Vol. VI: Statistics, Part A, (1984). Edited by Emlyn Lloyd, John Wiley and Sons. https://www.amazon.com/Handbook-Applicable-Mathematics-Statistics-6/dp/0471900249.
dc.relation.referencesen[5] J. H. Pollard. (1977) Handbook of Numerical and Statistical Techniques. Cambridge University Press. https://cc.bingj.com/cache.aspx?q=J.H.+Pollard.+(1977)+Handbook+of+Numerical+and+Statistical+Techniques.d=4579616625657925&mkt=en-WW&setlang=en-US&w=lYKqOOVXlYsikZD-qV7p9HJrRgt2oDA3.
dc.relation.referencesen[6] Applied Linear Regression, 3rd ed. Willey, Hoboken (2005). https://openlibrary.org/books/OL3306403M/Applied_linear_regression.
dc.relation.referencesen[7] J. R. Taylor (1982). An introduction to error analysis. University Science Books Mill Valley, California 1982. https://openlibrary.org/books/OL3786923M/An_introduction_to_error_analysis.
dc.relation.referencesen[8] B. Forbes (2009), Parameter estimation based on leastsquares methods. In F. Pavese and A. B. Forbes, editors, Data modeling for metrology and testing in measurement science, New York. Birkauser-Boston. https://link.springer.com/chapter/10.1007/978-0-8176-4804-6_5.
dc.relation.referencesen[9] G. Mejer (2008), Smart Sensor Systems. John Wiley, 2008. https://onlinelibrary.wiley.com/doi/book/10.1002/9780470866931.
dc.relation.referencesen[10] Evaluation of measurement data – Guide to the expression of uncertainty in measurement Joint Committee for Guides in Metrology, JCGM 100: 2008. https://www.iso.org/sites/JCGM/GUM/JCGM100/.
dc.relation.referencesen[11] JCGM 101:2008. Evaluation of measurement data – Supplement 1 to the ‘Guide to the Expression of Uncertainty in Measurement – propagation of distributions using a Monte Carlo method’. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP and OIML. https://www.bipm.org/documents/20126/2071204/JCGM.
dc.relation.referencesen[12] Dorozhovets M. Study of the effect of correlation of observation results on the uncertainty of linear regression. Pomiary, Automatyka, Kontrola. N12, 2008, s. 31–34 (in Polish). https://bibliotekanauki.pl/issues/8204.
dc.relation.referencesen[13] Dorozhovets M. Include measurement uncertainty of both quantities in linear regression. Pomiary, Automatyka, Kontrola. N9, 2008, pp. 612–615 (in Polish). https://bibliotekanauki.pl/issues/8089.
dc.relation.urihttps://archive.org/details/in.ernet.dli.2015.212877
dc.relation.urihttps://onlinelibrary.wiley.com/doi/book/10.1002/9781118625590
dc.relation.urihttps://doi.org/10.1007/b98890
dc.relation.urihttps://www.amazon.com/Handbook-Applicable-Mathematics-Statistics-6/dp/0471900249
dc.relation.urihttps://cc.bingj.com/cache.aspx?q=J.H.+Pollard.+(1977)+Handbook+of+Numerical+and+Statistical+Techniques.d=4579616625657925&mkt=en-WW&setlang=en-US&w=lYKqOOVXlYsikZD-qV7p9HJrRgt2oDA3
dc.relation.urihttps://openlibrary.org/books/OL3306403M/Applied_linear_regression
dc.relation.urihttps://openlibrary.org/books/OL3786923M/An_introduction_to_error_analysis
dc.relation.urihttps://link.springer.com/chapter/10.1007/978-0-8176-4804-6_5
dc.relation.urihttps://onlinelibrary.wiley.com/doi/book/10.1002/9780470866931
dc.relation.urihttps://www.iso.org/sites/JCGM/GUM/JCGM100/
dc.relation.urihttps://www.bipm.org/documents/20126/2071204/JCGM
dc.relation.urihttps://bibliotekanauki.pl/issues/8204
dc.relation.urihttps://bibliotekanauki.pl/issues/8089
dc.rights.holder© Національний університет “Львівська політехніка”, 2022
dc.subjectRegression
dc.subjectFunction
dc.subjectPolynomial
dc.subjectEstimation
dc.subjectSolution
dc.subjectStandard Deviation
dc.subjectUncertainty
dc.titleDirect solution of polynomial regression of order up to 3
dc.typeArticle

Files

Original bundle

Now showing 1 - 2 of 2
Thumbnail Image
Name:
2022v83n3_Dorozhovets_M-Direct_solution_of_polynomial_35-42.pdf
Size:
500.95 KB
Format:
Adobe Portable Document Format
Thumbnail Image
Name:
2022v83n3_Dorozhovets_M-Direct_solution_of_polynomial_35-42__COVER.png
Size:
1.29 MB
Format:
Portable Network Graphics

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.75 KB
Format:
Plain Text
Description: