Evaluating forest growth models
Effective model evaluation is not a single, simple procedure, but comprises several interrelated steps that cannot be separated from each other or from the purpose and process of model construction. We draw attention to several statistical and graphical procedures that may assist in model calibratio...
| Autores principales: | , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
1997
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/17641 |
| _version_ | 1855521277715939328 |
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| author | Vanclay, J.K. Skovsgaard, J.P. |
| author_browse | Skovsgaard, J.P. Vanclay, J.K. |
| author_facet | Vanclay, J.K. Skovsgaard, J.P. |
| author_sort | Vanclay, J.K. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Effective model evaluation is not a single, simple procedure, but comprises several interrelated steps that cannot be separated from each other or from the purpose and process of model construction. We draw attention to several statistical and graphical procedures that may assist in model calibration and evaluation, with special emphasis on those useful in forest growth modeling. We propose a five-step framework to examine logic and bio-logic, statistical properties, characteristics of errors, residuals, and sensitivity analyses. Empirical evaluations may be made with data used in fitting the model, and with additional data not previously used. We emphasize that the validity of conclusions drawn from all these assessments depends on the validity of assumptions underlying both the model and the evaluation. These principles should be kept in mind throughout model construction and evaluation. |
| format | Journal Article |
| id | CGSpace17641 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 1997 |
| publishDateRange | 1997 |
| publishDateSort | 1997 |
| record_format | dspace |
| spelling | CGSpace176412025-01-24T14:12:33Z Evaluating forest growth models Vanclay, J.K. Skovsgaard, J.P. growth models forests Effective model evaluation is not a single, simple procedure, but comprises several interrelated steps that cannot be separated from each other or from the purpose and process of model construction. We draw attention to several statistical and graphical procedures that may assist in model calibration and evaluation, with special emphasis on those useful in forest growth modeling. We propose a five-step framework to examine logic and bio-logic, statistical properties, characteristics of errors, residuals, and sensitivity analyses. Empirical evaluations may be made with data used in fitting the model, and with additional data not previously used. We emphasize that the validity of conclusions drawn from all these assessments depends on the validity of assumptions underlying both the model and the evaluation. These principles should be kept in mind throughout model construction and evaluation. 1997 2012-06-04T09:02:17Z 2012-06-04T09:02:17Z Journal Article https://hdl.handle.net/10568/17641 en Vanclay, J.K., Skovsgaard., J.P. 1997. Evaluating forest growth models . Ecological Modelling 98 :1-12. |
| spellingShingle | growth models forests Vanclay, J.K. Skovsgaard, J.P. Evaluating forest growth models |
| title | Evaluating forest growth models |
| title_full | Evaluating forest growth models |
| title_fullStr | Evaluating forest growth models |
| title_full_unstemmed | Evaluating forest growth models |
| title_short | Evaluating forest growth models |
| title_sort | evaluating forest growth models |
| topic | growth models forests |
| url | https://hdl.handle.net/10568/17641 |
| work_keys_str_mv | AT vanclayjk evaluatingforestgrowthmodels AT skovsgaardjp evaluatingforestgrowthmodels |