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標題: 連續型多樣性指標之模擬研究
A simulation study on continuous biodiversity indices
作者: 呂紫嫣
Lu, Tz-Yan
關鍵字: differential entropy

Shannon index
kernel estimator
nearst neighbor estimator
m-spacing estimator
Shannon 指標
出版社: 統計學研究所
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摘要: 測量生物多樣性指標,比較常用的有Simpson指標(1949)和Shannon指標(1948),常用來評估一群落中物種的組成和分布狀況,一般資料型態大都為離散型。但為了能更了解物種在生態系中的功能,或者在某些情況下資料並非離散型,例如:體重、體長……等,此時資料型態為連續的,因此傳統之多樣性指標並不適用。本文會回顧一些估計連續型Shannon指標的方法,以及試著使用拔靴法和Delta method去估計指標的標準差。最後本文利用電腦模擬評估各估計之表現。
Simpson index (Simpson, 1949) and Shannon index (Shannon, 1948) are two most widely used diversity indexes for measuring community structures. Most of diversity indexes in the literature are developed for dealing with categorical data (e.g. species counts). However, some research interest may focus on some variables with continuous type; for example, ecologists and biologists may concern the diversity regarding body sizes/weights of fishes, DBH's/heights of trees, etc. The present study is interested in evaluating some existing methods in the literature with such datasets. In addition, we have proposed some ways to construct the confidence intervals associated with those considered estimators. Based on the simulation study and data analysis with forest datasets, we have given some suggestions about the merits of the evaluated estimators.
其他識別: U0005-1107201112330300
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