Design‐based mapping of tree attributes by 3P sampling
| Autor: | Piermaria Corona, Sara Franceschi, Lorenzo Fattorini |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Statistics and Probability
Mean squared error Computer science Statistics as Topic Population 01 natural sciences prediction error interpolation Trees consistency inverse distance weighting interpolation marked finite populations simulation study 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Consistency (statistics) Inverse distance weighting 030212 general & internal medicine 0101 mathematics education education.field_of_study Ecology Estimator Sampling (statistics) General Medicine Tree (data structure) Statistics Probability and Uncertainty Algorithm Interpolation |
| Zdroj: | Biometrical Journal. 62:1810-1825 |
| ISSN: | 1521-4036 0323-3847 |
| DOI: | 10.1002/bimj.201900377 |
| Popis: | The estimation of individual values (marks) in a finite population of units (e.g., trees) scattered onto a survey region is considered under 3P sampling. For each unit, the mark is estimated by means of an inverse distance weighting interpolator. Conditions ensuring the design-based consistency of maps are considered under 3P sampling. A computationally simple mean squared error estimator is adopted. Because 3P sampling involves the prediction of marks for each unit in the population, prediction errors rather than marks can be interpolated. Then, marks are estimated by the predictions plus the interpolated errors. If predictions are good, prediction errors are more smoothed than raw marks so that the procedure is likely to better meet consistency requirements. The purpose of this paper is to provide theoretical and empirical evidence on the effectiveness of the interpolation based on prediction errors to prove that the proposed strategy is a tool of general validity for mapping forest stands. |
| Databáze: | OpenAIRE |
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