Modeling Population Growth in R with the biogrowth Package
The growth of populations is of interest in a broad variety of fields, such as epidemiology, economics or biology. Although a large variety of growth models are available in the scientific literature, their application usually requires advanced knowledge of mathematical programming and statistical...
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| Format: | Article |
| Language: | English |
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Foundation for Open Access Statistics
2023-09-01
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| Series: | Journal of Statistical Software |
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| Online Access: | https://www.jstatsoft.org/index.php/jss/article/view/4547 |
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| _version_ | 1846101711947563008 |
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| author | Alberto Garre Jeroen Koomen Heidy M. W. den Besten Marcel H. Zwietering |
| author_facet | Alberto Garre Jeroen Koomen Heidy M. W. den Besten Marcel H. Zwietering |
| author_sort | Alberto Garre |
| collection | DOAJ |
| description |
The growth of populations is of interest in a broad variety of fields, such as epidemiology, economics or biology. Although a large variety of growth models are available in the scientific literature, their application usually requires advanced knowledge of mathematical programming and statistical inference, especially when modelling growth under dynamic environmental conditions. This article presents the biogrowth package for R, which implements functions for modelling the growth of populations. It can predict growth under static or dynamic environments, considering the effect of an arbitrary number of environmental factors. Moreover, it can be used to fit growth models to data gathered under static or dynamic environmental conditions. The package allows the user to fix any model parameter prior to the fit, an approach that can mitigate identifiability issues associated to growth models. The package includes common S3 methods for visualization and statistical analysis (summary of the fit, predictions, . . . ), easing result interpretation. It also includes functions for model comparison/selection. We illustrate the functions in biogrowth using examples from food science and economy.
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| format | Article |
| id | doaj-art-936c686b92764b90b6c7c8056ede72c0 |
| institution | Kabale University |
| issn | 1548-7660 |
| language | English |
| publishDate | 2023-09-01 |
| publisher | Foundation for Open Access Statistics |
| record_format | Article |
| series | Journal of Statistical Software |
| spelling | doaj-art-936c686b92764b90b6c7c8056ede72c02024-12-29T00:12:49ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602023-09-01107110.18637/jss.v107.i01Modeling Population Growth in R with the biogrowth PackageAlberto Garre0Jeroen Koomen1Heidy M. W. den Besten2Marcel H. Zwietering3Wageningen University & ResearchWageningen University & ResearchWageningen University & ResearchWageningen University & Research The growth of populations is of interest in a broad variety of fields, such as epidemiology, economics or biology. Although a large variety of growth models are available in the scientific literature, their application usually requires advanced knowledge of mathematical programming and statistical inference, especially when modelling growth under dynamic environmental conditions. This article presents the biogrowth package for R, which implements functions for modelling the growth of populations. It can predict growth under static or dynamic environments, considering the effect of an arbitrary number of environmental factors. Moreover, it can be used to fit growth models to data gathered under static or dynamic environmental conditions. The package allows the user to fix any model parameter prior to the fit, an approach that can mitigate identifiability issues associated to growth models. The package includes common S3 methods for visualization and statistical analysis (summary of the fit, predictions, . . . ), easing result interpretation. It also includes functions for model comparison/selection. We illustrate the functions in biogrowth using examples from food science and economy. https://www.jstatsoft.org/index.php/jss/article/view/4547kinetic modellingmodel fittingpredictionsdynamic modellingRpredictive microbiology |
| spellingShingle | Alberto Garre Jeroen Koomen Heidy M. W. den Besten Marcel H. Zwietering Modeling Population Growth in R with the biogrowth Package Journal of Statistical Software kinetic modelling model fitting predictions dynamic modelling R predictive microbiology |
| title | Modeling Population Growth in R with the biogrowth Package |
| title_full | Modeling Population Growth in R with the biogrowth Package |
| title_fullStr | Modeling Population Growth in R with the biogrowth Package |
| title_full_unstemmed | Modeling Population Growth in R with the biogrowth Package |
| title_short | Modeling Population Growth in R with the biogrowth Package |
| title_sort | modeling population growth in r with the biogrowth package |
| topic | kinetic modelling model fitting predictions dynamic modelling R predictive microbiology |
| url | https://www.jstatsoft.org/index.php/jss/article/view/4547 |
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