The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A log gamma model and its maximum likelihood estimation
Abstract
A three parameter model is developed by reparameterizing and extending the distribution of the logarithm of a generalized gamma variate. The extreme value distributions for maxima and minima are included while the normal distribution is central. Asymptotic maximum likelihood theory is given and maximum likelihood distributions are studied, via simulation, in some special cases. A regression generalization is given.
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Citations
Cites
Handbook of Mathematical Functions
McQuarrie, D. A. (1966) · American Journal of Physics · doi:10.1119/1.1972842 · Cited by 40,433
Cited by
Statistical Size Distributions in Economics and Actuarial Sciences
Kleiber, C., & Kotz, S. (2003) · Wiley Series in Probability and Statistics · doi:10.1002/0471457175 · Cited by 1,117
flexsurv : A Platform for Parametric Survival Modeling in R
Jackson, C. (2016) · Journal of Statistical Software · doi:10.18637/jss.v070.i08 · Cited by 558
Bayesian Poisson regression for crowd counting
Chan, A. B., & Vasconcelos, N. (2009) · 2009 IEEE 12th International Conference on Computer Vision · doi:10.1109/iccv.2009.5459191 · Cited by 432
Metadata
- Authors
- PRENTICE, R. L.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 1974
- Volume
- 61
- Issue
- 3
- Pages
- 539-544
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W2023670977
- Cited by
- 327
- References
- 1
- FWCI
- 1.92
- Type
- journal article
- Language
- en
- Open access
- closed
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- PRENTICE, R. L. (1974). A log gamma model and its maximum likelihood estimation. Biometrika. https://doi.org/10.1093/biomet/61.3.539
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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.
