The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A maximum likelihood methodology for clusterwise linear regression
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Citations
Cites
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
Cited by
High-dimensional data clustering
Bouveyron, C., Girard, S., & Schmid, C. (2007) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2007.02.009 · Cited by 382
De Gieter, S., & Hofmans, J. (2015) · Human Resource Management Journal · doi:10.1111/1748-8583.12072 · Cited by 105
Hofmans, J., De Gieter, S., & Pepermans, R. (2013) · Journal of Vocational Behavior · doi:10.1016/j.jvb.2012.06.007 · Cited by 96
Metadata
- Authors
- DeSarbo, W. S., & Cron, W. L.
- Venue
- Journal of Classification
- Published
- 1988-09
- Volume
- 5
- Issue
- 2
- Pages
- 249-282
- ISSN
- 0176-4268 (ISSN-L)
- 1432-1343
- OpenAlex
- W2023689787
- Cited by
- 518
- References
- 2
- FWCI
- 2.90
- Type
- journal article
- Language
- en
- Open access
- green
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- CoChat. (2026). Citation check: A maximum likelihood methodology for clusterwise linear regression. https://app.cochat.ai/papers/10.1007/bf01897167
- The paper
- DeSarbo, W. S., & Cron, W. L. (1988). A maximum likelihood methodology for clusterwise linear regression. Journal of Classification. https://doi.org/10.1007/bf01897167
Data sources
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.
