A new approach for fitting growth models in random environment
Nonlinear growth models are widely employed in Animal sciences for describing growth of various species of animals. Nonlinear estimation procedures are generally employed for estimation of parameters. However, one limitation of these models is that they are applicable only when the data are availab...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Indian Council of Agricultural Research
2018-05-01
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| Series: | Indian Journal of Animal Sciences |
| Subjects: | |
| Online Access: | https://epubs.icar.org.in/index.php/IJAnS/article/view/79873 |
| _version_ | 1811169171402129408 |
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| author | PRAJNESHU PRAJNESHU HIMADRI GHOSH |
| author_facet | PRAJNESHU PRAJNESHU HIMADRI GHOSH |
| author_sort | PRAJNESHU PRAJNESHU |
| collection | DOAJ |
| description |
Nonlinear growth models are widely employed in Animal sciences for describing growth of various species of
animals. Nonlinear estimation procedures are generally employed for estimation of parameters. However, one
limitation of these models is that they are applicable only when the data are available at equidistant epochs. Another limitation is that the fluctuations in the system cannot be satisfactorily explained simply by adding an error term to the deterministic formulation. The purpose of this article is to bring to the notice of Animal scientists the new approach of Stochastic differential equation modelling, which is capable of incorporating both the above aspects. The methodology is discussed by considering Gompertz growth model. Relevant SAS codes for fitting the model are developed. Finally, the methodology is illustrated on secondary monthly pig weight data, collected at the
piggery farm of Indian Veterinary Research Institute, Izatnagar, Bareilly, India.
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| first_indexed | 2024-04-10T16:39:05Z |
| format | Article |
| id | doaj.art-927becf475a142b5b454ac00f3969776 |
| institution | Directory Open Access Journal |
| issn | 0367-8318 2394-3327 |
| language | English |
| last_indexed | 2024-04-10T16:39:05Z |
| publishDate | 2018-05-01 |
| publisher | Indian Council of Agricultural Research |
| record_format | Article |
| series | Indian Journal of Animal Sciences |
| spelling | doaj.art-927becf475a142b5b454ac00f39697762023-02-08T11:00:37ZengIndian Council of Agricultural ResearchIndian Journal of Animal Sciences0367-83182394-33272018-05-01871210.56093/ijans.v87i12.79873A new approach for fitting growth models in random environmentPRAJNESHU PRAJNESHU0HIMADRI GHOSH1ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012 IndiaICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012 India Nonlinear growth models are widely employed in Animal sciences for describing growth of various species of animals. Nonlinear estimation procedures are generally employed for estimation of parameters. However, one limitation of these models is that they are applicable only when the data are available at equidistant epochs. Another limitation is that the fluctuations in the system cannot be satisfactorily explained simply by adding an error term to the deterministic formulation. The purpose of this article is to bring to the notice of Animal scientists the new approach of Stochastic differential equation modelling, which is capable of incorporating both the above aspects. The methodology is discussed by considering Gompertz growth model. Relevant SAS codes for fitting the model are developed. Finally, the methodology is illustrated on secondary monthly pig weight data, collected at the piggery farm of Indian Veterinary Research Institute, Izatnagar, Bareilly, India. https://epubs.icar.org.in/index.php/IJAnS/article/view/79873Gompertz growth modelPig weight dataSAS software packageStochastic differential equation model |
| spellingShingle | PRAJNESHU PRAJNESHU HIMADRI GHOSH A new approach for fitting growth models in random environment Indian Journal of Animal Sciences Gompertz growth model Pig weight data SAS software package Stochastic differential equation model |
| title | A new approach for fitting growth models in random environment |
| title_full | A new approach for fitting growth models in random environment |
| title_fullStr | A new approach for fitting growth models in random environment |
| title_full_unstemmed | A new approach for fitting growth models in random environment |
| title_short | A new approach for fitting growth models in random environment |
| title_sort | new approach for fitting growth models in random environment |
| topic | Gompertz growth model Pig weight data SAS software package Stochastic differential equation model |
| url | https://epubs.icar.org.in/index.php/IJAnS/article/view/79873 |
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