International Research Journal of Agricultural Economics and Statistics

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Validation of two Parameter Function Height Diameter Models


Affiliations
1 Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Jammu (J&K), India
2 Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Kashmir (J&K), India
     

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Eleven nonlinear height diameter models were fitted and developed for Pinus trees based on individual tree height and diameter at breast height data (n=300) collected from block Langate of Kashmir province in India. Fitting of height diameter models using non-linear least square regression showed that all the parameters across all models were significant. In order to test the predictive performance of the models 10- folded cross-validation technique was used in this study. Comparison of AIC, RMSE, ME and Ad-R2 values for the training and validation data showed that most of the non-linear HD models capture the height diameter relationships for Pinus trees. Validation results suggest that Naslund -2 HD model provide the best height predictions in case of Pinus tree.

Keywords

Height, Diameter, Cross Validation, Pinus.
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  • Validation of two Parameter Function Height Diameter Models

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Authors

M. Iqbal Jeelani
Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Jammu (J&K), India
Manish Kr. Sharma
Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Jammu (J&K), India
Anil Bhat
Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Jammu (J&K), India
Mansha Gul
Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Kashmir (J&K), India

Abstract


Eleven nonlinear height diameter models were fitted and developed for Pinus trees based on individual tree height and diameter at breast height data (n=300) collected from block Langate of Kashmir province in India. Fitting of height diameter models using non-linear least square regression showed that all the parameters across all models were significant. In order to test the predictive performance of the models 10- folded cross-validation technique was used in this study. Comparison of AIC, RMSE, ME and Ad-R2 values for the training and validation data showed that most of the non-linear HD models capture the height diameter relationships for Pinus trees. Validation results suggest that Naslund -2 HD model provide the best height predictions in case of Pinus tree.

Keywords


Height, Diameter, Cross Validation, Pinus.

References