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研究生:張儀柔
研究生(外文):Yi-Jou Chang
論文名稱:非參數種類豐富度之估計整合方法
論文名稱(外文):A unified approach for the nonparametric species richness estimation
指導教授:黃文瀚黃文瀚引用關係
學位類別:碩士
校院名稱:國立中興大學
系所名稱:應用數學系所
學門:數學及統計學門
學類:數學學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:英文
論文頁數:41
中文關鍵詞:物種豐富度廣義摺刀估計樣本涵蓋區塊抽樣
外文關鍵詞:species richnessgeneralized jackknife methodsample coveragequadrat sampling
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對於生態或生物界的學者來說,物種種類豐富度估算,通常是個極重要的議題。很多科學家已經關注於這個問題很久了,對於這個部份的研究亦做了很多年。在這篇文章中,我們考慮估計群落之物種的種類豐富度問題,利用各種不同估計方法來估計,而估計方法都源起於廣義摺刀估計之架構。估計方法包含了樣本涵蓋、拔靴估計式、Chao1估計式等。同時,我們亦介紹某些情況下,比先前估計方法表現不錯的新估計方法。最後,我們將所有估計方法,利用模擬資料與實際資料來分析與比較。
Estimation of species richness in a local community is usually an important issue
for ecologists or biologists. Nowadays lots of scientists have been paying attention
to this topic very much. In this paper, our concern is how to estimate the number of
species (species richness) in a community. The generalized jackknife approach is of
great use to lessening the magnitude of bias of an estimator. Using this approach,
some popular richness estimators would be uni‾ed into a form of a speci‾c frame-
work. Speci‾cally, these estimators include the estimators by sample coverage, the
bootstrap estimator, and the Chao1 estimator. In addition, we also develop some
new estimators based on the same framework. A simulation study and some real
data analyses were carried out to evaluate the performance of all estimators we con-
cern.
1. Introduction 1
2. Generalized Jackknife Estimation 4
3. Replicated Incidence Data 9
4. Evaluation of The Estimators 12
5. Discussion 34
Appendix 36
References 39
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