Cost‐Efficient Density Estimation Based on Nearest Individual Distances in a Natural Forest | Zendy

Prayag V. R. | Zendy; Gore A. P. | Zendy

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Cost‐Efficient Density Estimation Based on Nearest Individual Distances in a Natural Forest

Author(s) -

Prayag V. R.,

Gore A. P.

Publication year - 1989

Publication title -

biometrical journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.108

H-Index - 63

eISSN - 1521-4036

pISSN - 0323-3847

DOI - 10.1002/bimj.4710310313

Subject(s) - estimator , mathematics , statistics , poisson distribution , density estimation , mean squared error , maximum likelihood , k nearest neighbors algorithm , tree (set theory) , point (geometry) , computer science , combinatorics , artificial intelligence , geometry

One useful method of estimating tree density is based on point to individual distances. Estimators are available for data on i ‐th nearest individual distances, i = 1, 2, 3,…, etc. This paper provides a method of deciding the optimal value of i in the sense of providing the maximum likelihood estimator of density with minimum mean square error subject to given outlay. The result derived for a Poisson forest is extended to an aggregated forest.

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