Taper equations based on nonlinear mixed effect modeling approach for Pinus nigra in Çankırı forests
In this study, statistical nonlinear mixed effect models were used to model taper of individual trees in Pinus nigra stands distributed within the Çankiri Forests. The data from 210 trees that were felled from Pinus nigra stands were used in this study. Three tree taper equations were fitted and eva...
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Universidad Austral de Chile, Facultad de Ciencias Forestales
2017
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oai:scielo:S0717-920020170003000122018-03-01Taper equations based on nonlinear mixed effect modeling approach for Pinus nigra in Çankırı forestsSenyurt,MuammerErcanli,IlkerBolat,Ferhat diameter estimate random parameters segmented polynomial model In this study, statistical nonlinear mixed effect models were used to model taper of individual trees in Pinus nigra stands distributed within the Çankiri Forests. The data from 210 trees that were felled from Pinus nigra stands were used in this study. Three tree taper equations were fitted and evaluated based on the sum square error (SSE), mean square error (MSE), root mean square error (RMSE) and the adjusted coefficient of determination (R²adj). The Jiang et al.'s equation was found to produce the most satisfactory fits with the SSE (4125.7), MSE (2.1771), RMSE (1.4755) and (0.976). The stem taper equation of Jiang et al. was used within the scope of mixed-effect model structures that involved both random and constant effect parameters. The nonlinear mixed-effect modeling approach for the stem taper equation of Jiang et al. with SSE (3254.8), MSE (1.71759), RMSE (1.3119) provided much better fitting and precise predictions than those produced by the nonlinear fixed effect model structures for this model. Within various sampling scenarios including different numbers of the sub-sample trees based on some sampling strategies from the validation data set, the sampling scheme with three top diameter sub-sample in a tree produced the best predictive results (SSE = 313.5321, MSE = 0.8637 and RMSE = 0.9345) in relation to the fixed effect predictions.info:eu-repo/semantics/openAccessUniversidad Austral de Chile, Facultad de Ciencias ForestalesBosque (Valdivia) v.38 n.3 20172017-01-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-92002017000300012en10.4067/S0717-92002017000300012 |
| institution |
Scielo Chile |
| collection |
Scielo Chile |
| language |
English |
| topic |
diameter estimate random parameters segmented polynomial model |
| spellingShingle |
diameter estimate random parameters segmented polynomial model Senyurt,Muammer Ercanli,Ilker Bolat,Ferhat Taper equations based on nonlinear mixed effect modeling approach for Pinus nigra in Çankırı forests |
| description |
In this study, statistical nonlinear mixed effect models were used to model taper of individual trees in Pinus nigra stands distributed within the Çankiri Forests. The data from 210 trees that were felled from Pinus nigra stands were used in this study. Three tree taper equations were fitted and evaluated based on the sum square error (SSE), mean square error (MSE), root mean square error (RMSE) and the adjusted coefficient of determination (R²adj). The Jiang et al.'s equation was found to produce the most satisfactory fits with the SSE (4125.7), MSE (2.1771), RMSE (1.4755) and (0.976). The stem taper equation of Jiang et al. was used within the scope of mixed-effect model structures that involved both random and constant effect parameters. The nonlinear mixed-effect modeling approach for the stem taper equation of Jiang et al. with SSE (3254.8), MSE (1.71759), RMSE (1.3119) provided much better fitting and precise predictions than those produced by the nonlinear fixed effect model structures for this model. Within various sampling scenarios including different numbers of the sub-sample trees based on some sampling strategies from the validation data set, the sampling scheme with three top diameter sub-sample in a tree produced the best predictive results (SSE = 313.5321, MSE = 0.8637 and RMSE = 0.9345) in relation to the fixed effect predictions. |
| author |
Senyurt,Muammer Ercanli,Ilker Bolat,Ferhat |
| author_facet |
Senyurt,Muammer Ercanli,Ilker Bolat,Ferhat |
| author_sort |
Senyurt,Muammer |
| title |
Taper equations based on nonlinear mixed effect modeling approach for Pinus nigra in Çankırı forests |
| title_short |
Taper equations based on nonlinear mixed effect modeling approach for Pinus nigra in Çankırı forests |
| title_full |
Taper equations based on nonlinear mixed effect modeling approach for Pinus nigra in Çankırı forests |
| title_fullStr |
Taper equations based on nonlinear mixed effect modeling approach for Pinus nigra in Çankırı forests |
| title_full_unstemmed |
Taper equations based on nonlinear mixed effect modeling approach for Pinus nigra in Çankırı forests |
| title_sort |
taper equations based on nonlinear mixed effect modeling approach for pinus nigra in çankırı forests |
| publisher |
Universidad Austral de Chile, Facultad de Ciencias Forestales |
| publishDate |
2017 |
| url |
http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-92002017000300012 |
| work_keys_str_mv |
AT senyurtmuammer taperequationsbasedonnonlinearmixedeffectmodelingapproachforpinusnigraincank305r305forests AT ercanliilker taperequationsbasedonnonlinearmixedeffectmodelingapproachforpinusnigraincank305r305forests AT bolatferhat taperequationsbasedonnonlinearmixedeffectmodelingapproachforpinusnigraincank305r305forests |
| _version_ |
1718444236308742144 |