A Yield prediction model for Pinus kesiya plantations in Chiengmai, Thailand / by Viroj Pimmanrojnagool
Material type:
TextLanguage: English Publication details: Los Baños, Laguna : 1979. Cavite State University- Main Campus,Description: 159 pages : illustrations ; 28 cmContent type: - text
- unmediated
- volume
- 634.9751 P64 1979
| Item type | Current library | Collection | Call number | Materials specified | URL | Status | Notes | Date due | Barcode |
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Theses / Manuscripts
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Ladislao N. Diwa Memorial Library Theses Section | Non-fiction | 634.9751 P64 1979 (Browse shelf(Opens below)) | Link to resource | Room use only | T-1495 | 00002348 |
Thesis (Ph.D. - - Forest Resources Mgt.) University of the Philippines, College, Laguna.
Includes bibliographical references.
PIMMANROJNAGOOL, VIROJ, University of the Philippines at Los Bafios, March, 1979. A Yield Prediction Model for Pinus kesiya Plantations in Chiang Mai, Thailand. Major Professor: Dr. Romulo A. del Castillo.
Yield prediction models with the use of a system of equations model was the primary subject of this study. The primary objective has been to explore the simultaneous equations model for yield prediction and compare it with the ordinary least squares method, and secondarily, to develop a yield prediction model for Pinus kesiya plantations in Chiengmai, Thailand.
The model presented in this study is composed of two equations, stand basal area and yield equations. Based on 247 10-meter radius circular plots located and measured in four Pinus kesiya plantations in Chiengmai, Thailand, the model was specified by the method of two-stage least squares and ordinary least squares.
With the management regime and genetic variation held constant, yield has been shown to be adequately explained by stand age, site index, original stand spacing, and stand basal area. The results obtained from deriving the model by both the methods of two-stage least squares and ordinary least squares were similar in some respects. First, the component equations of the model were found to be highly significant. The basal area and yield equations provided very high values of rR. Second, both methods provided similar yield curves which conform with the properties of a theoretical yield curve being S-shaped and satisfying the differentiation properties. Third, using the chi-square test of accuracy, both the methods of two-stage least squares and ordinary least squares gave the same level of accuracy which is within 11.5 percent of the true value at .05 significance level.
Theory, however, tells us that with a system of equations like the one developed in this study, the method of ordinary least squares gives inconsistent estimators while the two-stage least squares method provides consistent and asymptotically efficient estimators of the system parameters. As such, the results obtained by the method of two-stage least squares were used to specify the yield prediction model for the Pinus kesiya plantations in Chiengmai, Thailand.
A system of equations model without original stand spacing and a single equation model were also developed in this study for purposes of comparison. Based on the coefficient of determination, the properties of the theoretical yield curve, and level of accuracy, the two-stage least squares model gave slightly better results. The level of accuracy was higher by 0.9 percent for the proposed model than the model without original stand spacing, and higher by about 1.2 percent than the single equation model.
Submitted to the University Library 01/07/1994 T-1495