The Comparative R2 and its Application to Self-Referencing Models
Ključne riječi:
R-square, Coefficient of Determination, Fitting curves, Site models, Site IndexSažetak
The traditional coefficient of determination or R-square is the proportion of variation explained by a regression model versus the variation explained by the mean. This measure does not discriminate well between alternative self-referencing models such as site index curves. A generalized R-square based on the proportion of the variation explained by the self-referencing model versus the variation explained by a straight line through zero for each growth series provides better discrimination between candidate models. Three growth series from the South Africa Correlated Curve Trend Study are used to illustrate the difference between the traditional R-square and the generalized R-square.
Preuzimanja
Objavljeno
2012-09-30
Broj časopisa
Rubrika
Mathematical Modeling
Licenca
Authors who publish with this journal agree to the following terms:- Authors grant the journal right of first publication, with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) following the publication by the journal, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Kako citirati
The Comparative R2 and its Application to Self-Referencing Models. (2012). Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 4(2), Pages: 73-76 (4). https://mcfns.com/index.php/Journal/article/view/4.7
