Sensitivity Analysis for Gaussian-Associated Features Article Swipe
This paper is concerned with the evaluation of the uncertainties associated with Gaussian-associated features following the GUM methodology. We show how sensitivity matrices necessary for a GUM uncertainty evaluation can be calculated and how the variance matrices associated with the feature parameters can be estimated for a range of complete and partial features common in engineering. Example results are given in tables that allow practitioners to estimate, a priori, the uncertainties associated with fitted parameters, given a proposed measurement strategy for the case in which the point-cloud variance matrix is a multiple of the identity matrix. The sensitivity matrices can be used to evaluate the uncertainties for associated features for more general point-cloud variance matrices. All the calculations involved are direct and involve no optimization or Monte Carlo sampling; they can be implemented in spreadsheet software, for example.
Related Topics
Concepts
Variance (accounting)
Sensitivity (control systems)
Gaussian
A priori and a posteriori
Monte Carlo method
Computer science
Matrix (chemical analysis)
Range (aeronautics)
Algorithm
Mathematics
Data mining
Mathematical optimization
Statistics
Engineering
Aerospace engineering
Philosophy
Electronic engineering
Composite material
Quantum mechanics
Business
Materials science
Accounting
Epistemology
Physics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app12062808
- https://www.mdpi.com/2076-3417/12/6/2808/pdf?version=1646822083
- OA Status
- gold
- Cited By
- 6
- References
- 19
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4221032191
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4221032191Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/app12062808Digital Object Identifier
- Title
-
Sensitivity Analysis for Gaussian-Associated FeaturesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-03-09Full publication date if available
- Authors
-
Alistair ForbesList of authors in order
- Landing page
-
https://doi.org/10.3390/app12062808Publisher landing page
- PDF URL
-
https://www.mdpi.com/2076-3417/12/6/2808/pdf?version=1646822083Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2076-3417/12/6/2808/pdf?version=1646822083Direct OA link when available
- Concepts
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Variance (accounting), Sensitivity (control systems), Gaussian, A priori and a posteriori, Monte Carlo method, Computer science, Matrix (chemical analysis), Range (aeronautics), Algorithm, Mathematics, Data mining, Mathematical optimization, Statistics, Engineering, Aerospace engineering, Philosophy, Electronic engineering, Composite material, Quantum mechanics, Business, Materials science, Accounting, Epistemology, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
6Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 3, 2023: 1, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
19Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W4244159217, https://openalex.org/W2792600227, https://openalex.org/W2070539244, https://openalex.org/W2077676775, https://openalex.org/W2003754305, https://openalex.org/W2076948388, https://openalex.org/W3202771782, https://openalex.org/W3204142792, https://openalex.org/W657972686, https://openalex.org/W4391197160, https://openalex.org/W1619787994, https://openalex.org/W2482059038, https://openalex.org/W2018462997, https://openalex.org/W1987420617, https://openalex.org/W139497581, https://openalex.org/W2075788737, https://openalex.org/W2071794696, https://openalex.org/W2465509612, https://openalex.org/W4312258136 |
| referenced_works_count | 19 |
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| corresponding_author_ids | https://openalex.org/A5083084249 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 1 |
| corresponding_institution_ids | https://openalex.org/I134421475 |
| citation_normalized_percentile.value | 0.61970884 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |