Estimation of lacunarity using gamma regression model
In this study we evaluate estimated lacunarity in three different databases using the power (standard) and gamma model. Results showed that estimates of lacunarity using gamma regression model was superior to those with the power regression model. The gamma regression model had a higher coefficient...
| Autores: | , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | Brasil |
| Institución: | Universidade Estadual de Maringá (UEM) |
| Repositorio: | Acta scientiarum. Technology (Online) |
| Idioma: | inglés |
| OAI Identifier: | oai:periodicos.uem.br/ojs:article/41950 |
| Acceso en línea: | http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/41950 |
| Access Level: | acceso abierto |
| Palabra clave: | lacunarity; gamma model; fractal. |
| Sumario: | In this study we evaluate estimated lacunarity in three different databases using the power (standard) and gamma model. Results showed that estimates of lacunarity using gamma regression model was superior to those with the power regression model. The gamma regression model had a higher coefficient of model determination than the power regression model for all three used databases and, additionally, had smaller sums of residuals squared. The Gamma model was chosen the most appropriate model for lacunarity estimates. |
|---|