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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

遺傳演算法在門檻自迴歸模式(d,r)值估計的應用 / The Application of Genetic Algorithms in Parameters (d,r) Estimation of Threshold Autoregressions

張新發, Chang, Sin Fa Unknown Date (has links)
近幾年來,非線性時間數列分析有快速的發展。其中的門檻自迴歸模式(SETAR),以具有許多線性ARIMA模式所不能配適的特性而受到重視。但是,自1978年Tong建立SETAR模式以來,門檻參數估計的問題一直是SETAR模式在發展應用上的一個瓶頸。本文將探討以實數編碼遺傳演算法,結合統計學上的模式選取準則,建構SETAR模式門檻與延遲參數估計程序的可行性。並從這個基礎上,進一步地研究較精確的門檻參數估計法。 / Non-linear time series analysis has rapidly developed in recent years. Self-exciting threshold autoregression(SETAR) model of non-linear time series models is attentive, because it has some characters which linear ARIMA model fail to fit. But, It has not yet been applied widely because the question of estimation of threshold parameter limits its development and application since Tong proposed SETAR model in 1978. In this paper, we will study the feasibility which constructs a procedure of estimation of SETAR's threshod and delay parameters with real-coded genetic algorithm and statistical criterion of model selection, and develop a more precise estimation of threshold parameter in the basis.

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