Algorithms and software for fitting polynomial functions constrained to pass through the origin Article Swipe
I. M. Smith
,
Alistair Forbes
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/1065/21/212022
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/1065/21/212022
Fitting a polynomial function to data, accounting for uncertainty information associated with that data, is a problem that is commonly encountered in metrology and for which algorithms and software are widely available. For reasons of numerical stability, Chebyshev polynomials are often employed rather than monomials. The problem of fitting a polynomial function that is constrained to pass through the origin, again taking uncertainty information into account, which arises in a number of metrology areas, has not been addressed to the same extent. This paper describes algorithms to determine the best fit polynomial function passing through the origin to data, accounting for uncertainty, and using Chebyshev polynomials. Software that implements the algorithms, and is available free to download, is also described.
Related Topics
Concepts
Chebyshev polynomials
Polynomial
Chebyshev nodes
Monomial
Function (biology)
Software
Applied mathematics
Chebyshev filter
Mathematics
Algorithm
Stability (learning theory)
Curve fitting
Computer science
Mathematical optimization
Discrete mathematics
Mathematical analysis
Statistics
Programming language
Evolutionary biology
Machine learning
Biology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1742-6596/1065/21/212022
- OA Status
- diamond
- Cited By
- 3
- References
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2900829319
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2900829319Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1088/1742-6596/1065/21/212022Digital Object Identifier
- Title
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Algorithms and software for fitting polynomial functions constrained to pass through the originWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2018Year of publication
- Publication date
-
2018-08-01Full publication date if available
- Authors
-
I. M. Smith, Alistair ForbesList of authors in order
- Landing page
-
https://doi.org/10.1088/1742-6596/1065/21/212022Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
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diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1088/1742-6596/1065/21/212022Direct OA link when available
- Concepts
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Chebyshev polynomials, Polynomial, Chebyshev nodes, Monomial, Function (biology), Software, Applied mathematics, Chebyshev filter, Mathematics, Algorithm, Stability (learning theory), Curve fitting, Computer science, Mathematical optimization, Discrete mathematics, Mathematical analysis, Statistics, Programming language, Evolutionary biology, Machine learning, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 1, 2022: 1, 2021: 1Per-year citation counts (last 5 years)
- References (count)
-
1Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.accounting | 6, 99 |
| abstract_inverted_index.algorithms | 26, 85 |
| abstract_inverted_index.associated | 10 |
| abstract_inverted_index.available. | 31 |
| abstract_inverted_index.described. | 119 |
| abstract_inverted_index.implements | 108 |
| abstract_inverted_index.monomials. | 44 |
| abstract_inverted_index.polynomial | 2, 50, 91 |
| abstract_inverted_index.stability, | 36 |
| abstract_inverted_index.algorithms, | 110 |
| abstract_inverted_index.constrained | 54 |
| abstract_inverted_index.encountered | 20 |
| abstract_inverted_index.information | 9, 63 |
| abstract_inverted_index.polynomials | 38 |
| abstract_inverted_index.uncertainty | 8, 62 |
| abstract_inverted_index.polynomials. | 105 |
| abstract_inverted_index.uncertainty, | 101 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5026401250 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I134421475 |
| citation_normalized_percentile.value | 0.62059409 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |