Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/99156
標題: Estimation of abundance from presence–absence maps using cluster models
作者: Richard Huggins
Wen-Han Hwang
Jakub Stoklosa3
黃文瀚
關鍵字: Abundance;Clustering;Negative binomial;Presence–absence map
出版社: Environmental and Ecological Statistics
Project: Environmental and Ecological Statistics December 2018, Volume 25, Issue 4, pp 495–522
摘要: 
A presence–absence map consists of indicators of the occurrence or nonoccurrence of a given species in each cell over a grid, without counting the number of individuals in a cell once it is known it is occupied. They are commonly used to estimate the distribution of a species, but our interest is in using these data to estimate the abundance of the species. In practice, certain types of species (in particular flora types) may be spatially clustered. For example, some plant communities will naturally group together according to similar environmental characteristics within a given area. To estimate abundance, we develop an approach based on clustered negative binomial models with unknown cluster sizes. Our approach uses working clusters of cells to construct an estimator which we show is consistent. We also introduce a new concept called super-clustering used to estimate components of the standard errors and interval estimators. A simulation study is conducted to examine the performance of the estimators and they are applied to real data.
URI: http://hdl.handle.net/11455/99156
DOI: 10.1007/s10651-018-0415-5
Appears in Collections:統計學研究所

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