散在重復序列 的英文怎麼說

中文拼音 [sǎnzàizhòngfùxùliè]
散在重復序列 英文
interspersed repeat sequence
  • 散 : 散動詞1. （由聚集而分離） break up; disperse 2. （散布） distribute; disseminate; give out 3. （排除） dispel; let out
  • 重 : 重Ⅰ名詞（重量; 分量） weight Ⅱ動詞（重視） lay [place put] stress on; place value upon; attach im...
  • 復 : Ⅰ形容詞1 （重復） repeated; double; duplicate 2 （繁復） complex; compound Ⅱ動詞1 （轉過去或轉過...
  • 列 : Ⅰ動1 （排列） arrange; form a line; line up 2 （安排到某類事物之中） list; enter in a list Ⅱ名詞1...
  • 重復 : 1 repeat; duplicate; reduplicate; iterate 2 repetition; reiteration; gemination; rerun; duplicati...
  1. Repetitive sequences make up a significant fraction of genomes. according to the way they are arranged, repetitive sequences can be generally classified into two large groups : tandem repeat and dispersed repeat

    重復序列在基因組中廣泛存在，按照重復單元的排列方式，可將它分為串聯重復序列和散在重復序列兩大類。
  2. In this essay, firstly the author analyzes the predictability of time series from china ' s stock exchange using three kinds of methods : arma model, neural network model and non - parametric estimation and gives evaluation on their performances while at the same time puts forward some conclusions deserving attention from both stock exchange supervising department and stock traders. secondly, the author examines the assumptions closely on which the above - said methods base and gives a detailed discussion on them, especially using garch model to test quantitatively the stability of china ' s stock exchange, afterwards drawing the conclusion that it is hard to make accurate prediction of price or return rate of china ' s stocks for none of the assumptions fully holds ground. thirdly, taking account of the difference between chinese stock traders as a whole and that of developed countries, the author gives a thorough analysis on the complexity and volatility of its ( traders " ) reaction to information and points out that the intrinsic heterogeneous and volatile reaction to information is an important reason for the almost unpredictability of the price or return rate in china ' s stock exchange

    本文首先採用arma模型、非參數模型以及神經網路模型對我國股市時間序列進行研究，對三種方法在分析我國股市時間序列的表現進行評價，並得出了一些對監管部門以及股票交易者有借鑒意義的結論；其次作者對三種模型分析我國股市時間序列的前提進行了討論，特別是利用garch模型對我國股市的系統穩定性進行了量化檢驗，得出了前提難以滿足導致準確預測我國股市價格或收益率困難的結論；第三，考慮到中國股市股票交易者群體與發達國家股市股票交易者群體之間的差異，作者借用行為金融學的理論成果對我國股票交易者對信息反應的復雜性和易變性進行了詳細分析，指出股票交易者對信息反應的異質性和易變性是造成難以準確預測我國股市的一個重要原因，考慮到我國股市以散戶為主導的特性將長期存在，因此將行為金融學的研究結論納入對我國股市時間序列的量化研究具有重要的意義；最後，作者從唯理預測與唯象預測之間差異的角度出發，指出了唯象預測的缺點並對我國股市時間序列的研究方向進行了展望。
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