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Weighted Least Squares Fitting Using Ordinary Least Squares Algorithms
Abstract
A general approach for fitting a model to a data matrix by weighted least squares (WLS) is studied. This approach consists of iteratively performing (steps of) existing algorithms for ordinary least squares (OLS) fitting of the same model. The approach is based on minimizing a function that majorizes the WLS loss function. The generality of the approach implies that, for every model for which an OLS fitting algorithm is available, the present approach yields a WLS fitting algorithm. In the special case where the WLS weight matrix is binary, the approach reduces to missing data imputation.
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Cited by
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Cai, C., Li, G., Chi, Y., Poor, H. V., & Chen, Y. (2021) · The Annals of Statistics · doi:10.1214/20-aos1986 · Cited by 37
An investigation into the effectiveness of using acoustic touch to assist people who are blind
Zhu, H. Y., Hossain, S. N., Jin, C., Singh, A. K., Nguyen, M. T. D., Deverell, L., Nguyen, V., Gates, F. S., Fernandez, I. G., Melencio, M. V., et al. (2023) · PLoS ONE · doi:10.1371/journal.pone.0290431 · Cited by 16
Metadata
- Authors
- Kiers, H. A. L.
- Venue
- Psychometrika
- Publisher
- Cambridge University Press (CUP)
- Published
- 1997-06
- Volume
- 62
- Issue
- 2
- Pages
- 251-266
- ISSN
- 0033-3123 (ISSN-L)
- 1860-0980
- OpenAlex
- W2140968209
- Cited by
- 199
- References
- 0
- FWCI
- 3.79
- Type
- journal article
- Language
- en
- Open access
- closed
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- Kiers, H. A. L. (1997). Weighted Least Squares Fitting Using Ordinary Least Squares Algorithms. Psychometrika. https://doi.org/10.1007/bf02295279
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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).
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