近幾年來，非線性時間數列轉折點的研究愈來愈受到重視，學者們也提出許多關於轉折點的偵測及檢定方法。若考慮實際資料走勢轉變的情形，“轉折區間”的概念更可以解釋結構改變的現象。但文獻中對於如何找尋時間數列結構改變之轉折區間的研究並不多。本文擬以時間數列統計模式及模糊學理論的角度來研究，並結合遺傳演算的規則而提出主導模式的概念，來架構出時間數列遺傳模式，再藉由轉折區間決策法則來找出數列的轉折區間。其中，我們以統計模式為遺傳演化過程中的染色體，而以候選模式之隸屬度函數為衡量染色體適應能力的指標。最後，我們舉出臺灣股價收盤指數之實例，分別以我們所提出的方法及其他方法找出數列的轉折區間及轉折點，並做比較。 / For recent years, the research of change point in nonlinear time series has been considered to be more and more important. Scholars have proposed a lot of detecting and testing methods about change points.If considering the trend of real situation, the concept of change period will show the phenomena of structure change.But there are not many researches about how to find change period in time series.My paper is based on the points of time series models and fuzzy theory.Besides,it combines the rules of genetic algorithm and provides the concepts of leading model to construct time seriep genetic model and to find out change period by decision rule.ln this paper, we use time series statistical models as chromosome in procedure of genetic evolution, and we also use membership function of selected models as pereformance: index of chromosome.Finally, the empirical application about change periods and change points detecting by our method and other's for Taiwan stock closing prices is demonstrated and make a comparision with these results.

本研究的目的在暸解教師流動的型態與調動的因素，從83學年度臺灣省國民中學調動教師中抽取384人，並同時抽取380位未調動教師作為參照。 　　本研究採用虛擬依變項的迴歸分析，探討導致教師調動的因素。結果發現教師調動的型態存在往都會地區流動的現象。調動與非調動教師的比較中，在性別、教學年資、婚姻狀況與配偶的勞動參與率、自用住宅的擁有、調動次數、學校規模、以及是否為居民的變項上有顯著的不同。 　　在調動機率的影響方面，性別、教學年資、婚姻狀況與配偶的勞動參與率、調動次數、學校規模、以及薪資與福利措施的滿意度上，有著顯著的預測力。研究的結論是教育人力資源分配仍不平均，從影響教師調動機率的因素中，可以提供導引教育人力資源分配更加均衡的線索。 / The main purpose of this study is to inquire into the style about the teachers' mobility and the factors affecting such mobility. Sampling from 1994 academic year in Taiwan, the researcher focuses on the 384 cases of all mobilized teachers and their counterpart-380 nonmobilized cases. 　　A dummy dependent regression analysis is conducted to explore the factors. As a result, the phenomenon for mobility tends to flow into the metropolis. Factors affecting the mobility exhibits significant differences compared to nonmobility; such as factors among sex, seniority, marriage, inhibition, frequcncy of mobility and the scale of the school. 　　In additions, the propensity to mobile, as this study finds, has to do with their sex, seniority, marriage and the labor participation of spouse, frequcency of mobility, degree of the content about their wages and welfare, and the scale of the school. The conclusions made here are: the human resources in education is still scanty. From the factors influenced mobility probability, it can provide some clues to make the human resources in education more equal.

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.

近幾年來，非線性時間數列分析一直是時間數列及計量經濟學者所熱衷的研究主題之一，而非線性時間數列結構改變的研究也越來越受到重視。其中的門檻自迴歸模式，雖具有線性模式所不能配適的特性，但模式建構的問題，一直是其在發展應用上的瓶頸。本研究擬以門檻自迴歸模式建構的流程並結合遺傳演算法的最佳化搜尋技術，架構出時間數列遺傳演算法，藉此演算法則及程序，全域性地搜尋最佳的門檻自迴歸模式。 / Non-linear time series analysis is a research topic which the schalors of time series and econometrics are intent on, and the research of structure change of non-linear time series is attentive. Threshold autoregressive model (TAR model) of non-linear time series has some characters which linear model fail to fit while the problem of how to find an appropriate threshold value is still attracted many researchers attention. In this paper, we present about searching the parameters for a TAR model by genetic algorithms.

The main purpose of this study is to inquire into the style about the teachers' mobility and the factors affecting such mobility. Sampling from 1994 academic year in Taiwan, the researcher focuses on the 384 cases of all mobilized teachers and their counterpart-380 nonmobilized cases. A dummy dependent regression analysis is conducted to explore the factors. As a result, the phenomenon for mobility tends to flow into the metropolis. Factors affecting the mobility exhibits significant differences compared to nonmobility; such as factors among sex, seniority, marriage, inhibition, frequcncy of mobility and the scale of the school. In additions, the propensity to mobile, as this study finds, has to do with their sex, seniority, marriage and the labor participation of spouse, frequcency of mobility, degree of the content about their wages and welfare, and the scale of the school. The conclusions made here are: the human resources in education is still scanty. From the factors influenced mobility probability, it can provide some clues to make the human resources in education more equal.

公共支出與公共收入乃為一體兩面之事。A.C. Pigou於1947年就曾提出租稅融通方式不同，將影響公共支出水準的看法，他並且認為當政府採用扭曲性租稅來融通公共財時，會產生超額負擔使得公共財提供的邊際成本增加。基於這項觀點，就不宜再以公共財的直接成本作為最適公共支出水準的依據，而應將扭曲性租稅本身可能造成的扭曲效果納入考慮。而這也表示了P.A. Samuelson於1954年提出的最適公共財提供條件ΣMRS=MRT應該被修正，且視融通公共財的租稅方式所產生的影響而應有不同的最適公共財提供條件。 　　本篇論文的目的，即在討論各種不同的租稅制度融通下，以最適公共財提供條件的修正，分析修正項目對最適公共支出水準的影響，並與過去的文獻作一比較，以期得出不同的租稅制度融通和最適公共支出之間的關係。

本文採用傅利葉轉換與小波轉換以探討非線性現象：長期相依的碎形結構與混沌現象。藉由傅利葉轉換與小波轉換兩種研究方法，所得到臺灣股票市場加權股價指數的實證結論如下：1.藉由傅利葉轉換所得到的H值為0.4632；藉由小波轉換所得到的H值為0.4750。這兩種研究方法皆顯示臺灣股票市場具有負的長期相依的碎形結構。2.藉由傅利葉轉換的研究方法，臺灣股票市場加權股價指數的頻譜由初始向下與寬的連續的頻帶所組成；臺灣股票市場加權股價指數的自我相關函數則隨著時間差距的增加而遞減。此顯示臺灣股票市場具有混沌現象。3.小波轉換可以檢測出臺灣股票市場加權股價指數的奇異之處，並且指出存有一能說明臺灣股票市場碎形結構的複雜性的機制。藉由以上的實證結論，可以得知臺灣股票市場具有反持續性的碎形結構，股票價格的變動來自於臺灣股票市場尺度上的自我相似性。即使如此，由於混沌不可預測性的本質，使得股票價格的預測似乎是不可能的。 / The Fourier transform and the wavelet transform are utilized in this research to explore the nonlinear phenomena: the fractal structure of long trem dependence and the phenomenon of chaos. 　　In terms of the two research methods of the Fourier transform and the wavelet transform, the empirical conclusions of the Taiwan stock exchange weighted stock index are derived as follows: 　　1. The $H$ value of the research method of the Fourier transform is 0.4632; the $H$ value of the research method of the wavelet transform is 0.4750. The two research methods show that the Taiwan stock market has a fractal structure of negative long term dependence. 　　2. In terms of the research method of the Fourier transform, the power spectrum of the Taiwan stock exchange weighted stock index consists of initially downward and wide continuous band of frequencies; the autocorrelation function of the Taiwan stock exchange weighted stock index decreases as the time lag increases. These observations show that there exists the phenomenon of chaos in the Taiwan stock market. 　　3. The wavelet transform can detect out the singularities of the Taiwan stock exchange weighted stock index and can point out the heirarchy that illustrates the complexity of the fractal sturcture in the Taiwan stock market. 　　By the above empirical conclusions, there exists the antipersistent fractal structure in the Taiwan stock market. The variations of stock prices result from the self-similarity of the scales of the Taiwan stock market. Even so, the prediction of stock prices seems very impossible as a result of the unpredictability of chaotic nature.

當我們利用Shewhart管制圖(Shewhart control chart)或累積和管制圖(Cumulative-sum chart. CUSUM chart)來偵測製程時,通常假設製品係獨立取自一個服從均數μ和標準差為σ的獨立常態分配的管制下進行。但是若產品特性值呈現自相關時,這類管制圖就可能發生誤導的結果。本文利用時間序列模式來解決具相關變數的管制圖問題。並考慮利用非線性時間序列模式及特別原因管制圖(special-cause control chart)來檢視台灣經濟景氣指標是否處於控制中的狀態。並討論特別原因管制圖的連串長度分佈(run length distribution)。在最後的實例分析中,介紹自動控制的觀念。 / Traditionally, in the quality control process, such as: Shewhart control chart or CUSUM chart, it is assumed that the observation process follows an i.i.d normal distribution. If the assumption for independence fails, that is when the process exhibits type of autocorrelation, we need to find a more reliable decision method. In this paper, we will apply the time series analysis and structure changed concept to slove the serial correlation problem. The idea of automatic control can be applied in the explanation of this nonlinear process. Finally, a time series about the monitoring indicators of Taiwan is discussed in detail as an example.

假設二元反應曲線為簡單線性羅吉斯迴歸模型(Simple Linear Logistic Regression Model)，在樣本數為偶數的前題下，所謂的最佳D型設計(D-Optimal Design)是直接將半數的樣本點配置在第17.6個百分位數，而另一半則配置在第82.4個百分位數。很遺憾的是，這兩個位置在參數未知的情況下是無法決定的，因此逐次實驗設計法(Sequential Experimental Designs)在應用上就有其必要性。在大樣本的情況下，本文所探討的逐次實驗設計法在理論上具有良好的漸近最佳D型性質(Asymptotic D-Optimality)。尤其重要的是，這些特性並不會因為起始階段的配置不盡理想而消失，影響的只是收斂的快慢而已。但是在實際應用上，這些大樣本的理想性質卻不是我們關注的焦點。實驗步驟收斂速度的快慢，在小樣本的考慮下有決定性的重要性。基於這樣的考量，本文將提出三種起始階段設計的方法並透過模擬比較它們之間的優劣性。 / The D-optimal design is well known to be a two-point design for the simple linear logistic regression function model. Specif-ically , one half of the design points are allocated at the 17.6- th percentile, and the other half at the 82.4-th percentile. Since the locations of the two design points depend on the unknown parameters, the actual 2-locations can not be obtained. In order to dilemma, a sequential design is somehow necessary in practice. Sequential designs disscused in this context have some good properties that would not disappear even the initial stgae is not good enough under large sample size. The speed of converges of the sequential designs is influenced by the initial stage imposed under small sample size. Based on this, three initial stages will be provided in this study and will be compared through simulation conducted by C++ language.

線性結構關係模式是一種考慮以多個直線方程式來分析處理變數間因果關 係的統計方法，其結合了因徑分析及因素分析之優點並將之融合於整體模 式中。線性結構關係模式經過參數估計後，需評估整個模式之好壞，因此 許多學者嘗試提出一些評估模式好壞的適合度指標，如一般常用的卡方檢 定、殘差均方根、適合度指標、調整後適合度指標以及基準指標等。這些 指標中有的指標會受到樣本數大小或樣本分布的影響，有些指標受模式隱 藏變數多寡或因素指標多寡的影響，有些指標需有嚴格的條件（如樣本需 服從常態分布）及前提方可適用，且有些指標的分布是未知的，因此欲對 這些指標進行區間估計、假設檢定、或顯著性差異比較是不可能的。基於 上述各種適合度指標的缺點，本論文利用拔靴法進行重抽樣求得拔靴分布 來解決上述各種問題。然而傳統的拔靴法在線性結構關係模式上是不適用 的，因此，再提出一改良拔靴法程序，求得拔靴分布來做為評估模式好壞 的依據，並利用改良拔靴法來做巢狀模式之顯著性差異比較及利用抽樣誤 差和非抽樣誤差觀念來評估模式適合度。