Sample-Plot Size and Diameter Moments/Percentiles Prediction Model Effects on Stand Diameter Distribution Recovery Accuracy
<p>There have been several studies that aim to determine the most superior Weibull parameter recovery approach of specifying a given forest stands Weibull diameter distribution, but no consensus has been made. The lack of agreement could be attributed to studies using different moments/percent...
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Other Authors: | |
Format: | Others |
Language: | en |
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MSSTATE
2019
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Online Access: | http://sun.library.msstate.edu/ETD-db/theses/available/etd-03182019-100835/ |
Summary: | <p>There have been several studies that aim to determine the most superior Weibull parameter recovery approach of specifying a given forest stands Weibull diameter distribution, but no consensus has been made. The lack of agreement could be attributed to studies using different moments/percentile prediction models as well as using different plot size data. This study investigates how plot size and prediction model form affects the performance for moments, hybrid, and percentile Weibull parameter recovery approaches. Five plot sizes and three moments/percentile prediction models were used to determine their effects. Weibull parameters were calculated using each recovery method for each plot size and moments/percentile prediction model combination. Each combinations diameter distribution was recovered and assessed using absolute error index. Results showed that plot size affected rank of precision for parameter recovery methods. Findings suggest that order statistics may be important in recovering Weibull distribution parameters from stand diameter summary statistics.</p> |
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