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Statistical Inference
Abstract
In the previous two chapters we discussed various mathematical models of random spatial patterns as well as of aggregates of randomly distributed objects (particles) of finite size. In order to relate these models to real complex patterns of material inhomogeneity statistical analysis of random fields and object patterns is necessary. As indicated in section 3.2.1, the first task is recognizing the basic features of a pattern and selection of a suitable model to represent the data. Then follows the problem of parameter estimation for the chosen random field using the available data. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Citations
Cited by
Kang, L., Chen, W., Petrick, N. A., & Gallas, B. D. (2015) · Statistics in Medicine · doi:10.1002/sim.6370 · Cited by 420
Modeling continuous response variables using ordinal regression
Liu, Q., Shepherd, B. E., Li, C., & Harrell, F. E. (2017) · Statistics in Medicine · doi:10.1002/sim.7433 · Cited by 208
Statistical subspace-based damage detection with estimated reference
Viefhues, E., Döhler, M., Hille, F., & Mevel, L. (2022) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2021.108241 · Cited by 16
(2023) · doi:10.15620/cdc:124368 · Cited by 16
Metadata
- Authors
- Sobczyk, K., & Kirkner, D. J.
- Venue
- Modeling and Simulation in Science, Engineering and Technology
- Publisher
- Birkhäuser Boston
- Published
- 2001
- Pages
- 123-148
- ISSN
- 2164-3679 (ISSN-L)
- OpenAlex
- W4243531027
- Cited by
- 436
- References
- 0
- FWCI
- 7.89
- Type
- book chapter
- Language
- en
- Open access
- closed
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- Sobczyk, K., & Kirkner, D. J. (2001). Statistical Inference. Modeling and Simulation in Science, Engineering and Technology. https://doi.org/10.1007/978-1-4612-0121-2_5
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
