A note on the maximum likelihood estimator in the gamma regression model
This paper considers a nonlinear regression model, in which the dependent variable has the gamma distribution. A model is considered in which the shape parameter of the random variable is the sum of continuous and algebraically independent functions. The paper proves that there is exactly one maximu...
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| Format: | Article |
| Language: | English |
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AGH Univeristy of Science and Technology Press
2009-01-01
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| Series: | Opuscula Mathematica |
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| Online Access: | http://www.opuscula.agh.edu.pl/vol29/3/art/opuscula_math_2924.pdf |
| _version_ | 1818672706134999040 |
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| author | Jerzy P. Rydlewski |
| author_facet | Jerzy P. Rydlewski |
| author_sort | Jerzy P. Rydlewski |
| collection | DOAJ |
| description | This paper considers a nonlinear regression model, in which the dependent variable has the gamma distribution. A model is considered in which the shape parameter of the random variable is the sum of continuous and algebraically independent functions. The paper proves that there is exactly one maximum likelihood estimator for the gamma regression model. |
| first_indexed | 2024-12-17T07:44:09Z |
| format | Article |
| id | doaj.art-4ccff8a595a94cb6a79336b5a2e93c5f |
| institution | Directory Open Access Journal |
| issn | 1232-9274 |
| language | English |
| last_indexed | 2024-12-17T07:44:09Z |
| publishDate | 2009-01-01 |
| publisher | AGH Univeristy of Science and Technology Press |
| record_format | Article |
| series | Opuscula Mathematica |
| spelling | doaj.art-4ccff8a595a94cb6a79336b5a2e93c5f2022-12-21T21:58:03ZengAGH Univeristy of Science and Technology PressOpuscula Mathematica1232-92742009-01-01293305312http://dx.doi.org/10.7494/OpMath.2009.29.3.3052924A note on the maximum likelihood estimator in the gamma regression modelJerzy P. Rydlewski0AGH University of Science and Technology, Faculty of Applied Mathematics, al. Mickiewicza 30, 30-059 Krakow, PolandThis paper considers a nonlinear regression model, in which the dependent variable has the gamma distribution. A model is considered in which the shape parameter of the random variable is the sum of continuous and algebraically independent functions. The paper proves that there is exactly one maximum likelihood estimator for the gamma regression model.http://www.opuscula.agh.edu.pl/vol29/3/art/opuscula_math_2924.pdfgamma regressionnonlinear regressionmaximum likelihood estimatorshape parameter |
| spellingShingle | Jerzy P. Rydlewski A note on the maximum likelihood estimator in the gamma regression model Opuscula Mathematica gamma regression nonlinear regression maximum likelihood estimator shape parameter |
| title | A note on the maximum likelihood estimator in the gamma regression model |
| title_full | A note on the maximum likelihood estimator in the gamma regression model |
| title_fullStr | A note on the maximum likelihood estimator in the gamma regression model |
| title_full_unstemmed | A note on the maximum likelihood estimator in the gamma regression model |
| title_short | A note on the maximum likelihood estimator in the gamma regression model |
| title_sort | note on the maximum likelihood estimator in the gamma regression model |
| topic | gamma regression nonlinear regression maximum likelihood estimator shape parameter |
| url | http://www.opuscula.agh.edu.pl/vol29/3/art/opuscula_math_2924.pdf |
| work_keys_str_mv | AT jerzyprydlewski anoteonthemaximumlikelihoodestimatorinthegammaregressionmodel AT jerzyprydlewski noteonthemaximumlikelihoodestimatorinthegammaregressionmodel |