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    請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/3844


    題名: 對動物認知過程做整體推論所必須要的資料型態及分析之探討--以豆象之產卵行為為例
    其他題名: What Data Types and Analyses are Appropriate for Coherent Inferences on Animal Cognitive Processing---Illustrated by Female Bean Weevils Oviposition Processes
    作者: 蔡紋琦
    關鍵詞: 訊息;模組;策略;最大擬似;認知行為
    Information;Template;Oviposition Selection Tactic;Maximum likelihood;Cognition
    日期: 2002
    上傳時間: 2007-04-18 16:36:44 (UTC+8)
    出版者: 臺北市：國立政治大學統計學系
    摘要: 很多實驗由於預算上的限制或技術上執行的困難，我們只能在離散的時間點或在某個特定事件發生時的時間點才能對實驗對象做資料的觀察或截取，然後再將手上這份低維結構的資料拿去做分析。但若決定資料取捨的機制和我們所希望下推論的方向有關時，低維結構的資料就可能帶給我們錯誤的訊息，在這種情況下，或許就必須要花費較多的精力去求得高維模組的資料以得到正確的結論。我們考慮一個由洪和謝所主持的實驗，這個實驗是希望找出母豆象選擇豆子產卵的策略。根據實驗的設計，兩種不同層次的可能模組可被考慮，一個是日模組，另一個是路徑模組。第一個模組不管是從經費或人力資源方面來看，都是比較容易執行取得但其所夾帶的資訊卻少且包含於第二個模組。我們希望藉由電腦模擬去比較是否兩種模組資料都帶給我們一樣好或壞的決策選擇或者是有必要去執行取得第二個較困難但精確的路徑模組。由電腦模擬的結果，我們發現不管是給定日模組資料或是路徑模組資料，正確的決策都產生較大的最大擬似值，且其和錯誤決策所產生的最大擬似值的比值都差不多一樣大。換言之，低維結構和高維模組兩種資料都給我們一樣好的決策選擇，所以原來根據日模組資料所下的推論是可信賴的，不須要再設法取得更細緻形態的模組資料。
    Due to the limitation on budget or technicality, the state of the investigated subject in an experiment usually is recorded only at a discrete time scale or at the time when a certain event occurs. The analysis will then carried out based on the data set of the lower level structure rather than the complete high dimensional temporal platform. If the inference we wish to make is related to the recording switch of a certain event, the lower level structure of data set may conclude incorrect inference and hence it will be worth to make effort on obtaining a higher level of data set. A simulation is run based on the data collected from an experiment conducted by Horng and Hsieh. In the experiment, they are interested in which strategy that a female bean weevil may use to select their oviposition hosts. Depending on the design of the experiment, two possible levels of data set can be obtained: daily template, or additionally, path template. The daily template is much easier to be observed than the path template. However it contains less information. The simulation trintends to see whether or not these two different levels of data set bring the same information. If not, a new experiment to obtain a higher level of data set may need to be executed. The simulation shows that the maximum likelihood value under the true strategy is always larger than the false strategy no matter which level of data set is given and the likelihood ratio magnitude is about the same. This supports us the inference drawn from the lower dimensional structure of data set.
    描述: 核定金額：118800元
    資料類型: report
    顯示於類別:[統計學系] 國科會研究計畫

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    912118M004007.pdf30KbAdobe PDF21184檢視/開啟


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