arma model 中文意思是什麼
arma model
解釋
自回歸移動平均數混合模型-
The analysis of monetary constitution indicates : the foundation currency is strongly controllable and the currency multiplicator isn ’ t controllable, but it could be well and truly forecasted by the arma model, thus it ’ s strongly predictable
從貨幣供應量的構成分析:基礎貨幣具有較強的可控性;貨幣乘數不具有可控性，但貨幣乘數可以利用arma模型進行較為準確的預測，具有較強的可預測性。 -
We analyse the dispersion of stock returns and have the tests of serial correlation. the results show that the trading mechanism has a significant effect on a number of characteristics of stock returns. first, the distribution of open - to - open returns has greater variance than that of close - to - close returns. second. the serial correlation pattern is quite different in the two return series. the open - to - open returns have negative autocorrelation coefficient, but the close - to - close returns is positive. further, employing an arma ( 1, 1 ) model we find that in the opening. returns exhibit higher residual noise and stronger dependence on past returns, reflecting stronger deviations from the random - walk form of the market efficiency hypothesis
主要表現為：一，開盤收益序列比收盤收益序列具有更大的方差。二，兩種收益序列的序列相關形式不同，開盤收益序列表現為負相關，而收盤收益序列表現為正相關。而且我們通過arma （ 1 ， 1 ）模型的進一步檢驗，發現開盤收益序列比收盤收益序列具有更大的殘差，更依賴于過去的收益序列，也更偏離於市場有效的隨機遊走形式的假設。 -
Based on the rv - arma model, it is discussed that the persistence of conditional variances has a effect on capital asset pricing model ( capm ) from persistence viewpoint
在「已實現」波動自回歸移動平均模型基礎上，從條件方差持續性的角度，討論了條件方差的持續性對資產資本定價模型的影響。 -
Here we developed the general arma ( p, q ) - garch ( r, s ) - m ( k ) models, which maybe become increasingly important for estimating volatility returns and exogenous shocks for finance data. after we present the posterior distribution of the model and the full conditional distributions of all the parameters of the model, we develop a hybrid metropolis - hastings algorithm for estimating the parameters of arma - garch - m models based on the works of bayesian chib and greenberg ( 1994 ) and nakatsuma ( 2000 ). here we simplified the estimations in ma and garch block
作為該模型的推廣，我們在本文中提出了一個一般的arma （ p ， q ） - garch （ r ， s ） - m （ k ）模型，並在詳細給出模型的后驗分佈以及模型的所有參數的滿條件分佈的基礎上，結合chibandgreenberg （ 1994 ）與nakatsuma （ 2000 ）等人的工作，對此新模型設計了一個可行的混合metropolis - hastings演算法，簡化了ma塊與garch塊的估計。 -
Then the dynamic weighing system is equivalent to system that is time changeing and non - linearity syetem, dynamic mathmatic model is established by analysis. for the system is the arma model, parameter identification method of adaptive least square based on householder transformation is adopted
然後，將動態稱重系統等效為二階系統，分析得出了系統為時變非線性系統，推導出了其動態數學模型，並且根據系統為arma模型，將問題轉化為參數辨識問題。 -
Arma predictive model based celp speech coding algorithm
基於零極點預測模型的碼激勵線性預測語音編碼演算法 -
Abstract : in this paper we analyse some predictation approaches of random time series and by using arma model we predict effectually the weighted aggregative indexes of securities market in shanghai and shenzhen
文摘:分析了隨機時間序列的統計預測方法，並利用arma模型對深滬市未來短期指數進行了有效預報。 -
Dynamic weighing system is as a second - order system and set it up model, then has its transform function laplace transform and z transform, at last has a formula that m is only relation to the system parameters. this article has system identified with the recursive least square ( rls ) method, and has the system parameters, while the auto - regressive - moving - average ( arma ) model for the second order weighing system is firstly derived. and has a equation which the mass is only correlation to the system parameters
論文具體分析了定量稱量問題，首先是把稱量系統看作是一個二階系統，建立數學模后，進行拉普拉斯變換和z變換后得出一個質量僅與系統參數有關的關系式，從而把稱量問題轉化為一個系統參數識別問題來解決。通過編寫的程序來採集系統信號並進行處理（運用漸消遞推最小二乘法）對系統參數進行識別，從而得出稱量結果。 -
By means of trigonometrical progression method and the mainline track spectrum, the sample function of the chinese mainline railway track random geometric irregularity is simulated. with the data obtained from track geometry inspection car on qinhuangdao - shenyang special line for passenger transport and arma time series model, the sample function of high - speed railway track random geometric irregularity are simulated. based on existing literature, the artificial bogie crawl waves at various different speeds are randomly simulated
根據我國干線鐵路軌道譜，採用三角級數法模擬出干線鐵路和準高速鐵路軌道不平順的樣本函數；根據秦沈客運專線高速試驗段軌檢車資料，採用arma時間序列模型模擬了高速鐵路軌道不平順隨機樣本函數；在既有研究資料的基礎上模擬出各種速度客車構架人工蛇行波；用隨機變量描述道床橫向剛度，並進行了隨機模擬；將振動理論和穩定理論結合建立系統的分析模型和運動方程；根據monte ? carlo法編制了車輛?軌道耦合系統隨機振動分析程序，進行了無縫線路隨機動力響應分析，通過試驗對計算模型、計算方法進行了驗證。 -
The paper applies time series analysis method to set up arma model and arima model
摘要運用時間序列分析方法對時間序列建立arma ， arima模型。 -
According to the needs of gps / sins integrated navigation algorithm, the error models of gps and sins are studied respectively. the autoregressive ( ar ) models and autoregressive moving average ( arma ) models of gps positioning error are established based on the analysis of the properties of static gps positioning error data. and the neural network method to determine the ar model parameters is given
根據gps / sins組合導航演算法的需要，分別對gps和捷聯系統的誤差模型進行了研究，在對gps靜態定位誤差數據特性分析的基礎上，建立了gps定位誤差的自回歸（ ar ）模型和自回歸滑動平均和（ arma ）模型，並用神經網路方法確定了ar模型參數。 -
5. the paper builds a new econometric model for estimating both the returns and durations, as well as gives the joint density of the marked point process of duration and transaction - by - transaction returns with an acd - arma framework
5 、在acd模型的基礎上引入arma模型，來描述交易的時間間隔和交易期間的收益兩個時間序列之間的相互關系，建立了acd - arma模型，給出了兩個變量之間的聯合分佈密度函數以及估計方法。 -
Study of reciprocating compressor condition forecasting based on arma model
模型的往復式壓縮機狀態預測 -
The work elicits a genetic algorithm that is utility to fit a arma structural model
論文中研究了用遺傳演算法對動態數據進行arma結構建模的問題。 -
This paper introduces two time - series models - arma model and arch model, which are adapt to the fluctuation forecast. i utilize the game theory and the chaos theory in the study of exchange rate fluctuation
繼之，本文將博弈論、混沌理論等理論引入匯率波動問題研究之中，研究了資本流動和匯率波動的博弈問題和匯率決定之混沌模型。 -
In this thesis, the ood method and such technologies as mfc, api, dll, and multi - thread will be talked about. secondly, pca and pls ca n ' t deal with time dependent data, and arma model can be used to solve this problem, but the problem of arma structural modeling must be solved
2 ）針對主元分析法、偏最小二乘法這兩種降維技術不能處理序列相關的動態數據的問題，可以用arma模型提取出動態數據中的序列獨立的擾動信號，但首先必須解決arma的結構建模問題。 -
( 4 ) the thesis converts unrest model ( arima model ) of time series to the rest model ( arma model ) of time series. it sets up models acrossing some procedures, such as model identify, factor estimation, model check, ect, then predict the development short - term warp of road foundation. it predicts the time of the filling soil of the next grade utilizing the growth theory of the strength of the road foundation, assures that the working organization and design go smoothly during the filling work of road foundation and saves time and money
（ 4 ）從路基實測變形數據出發，將時間序列非平穩性模型（ arima模型）轉化成時間序列平穩模型（ arma模型） ，通過模型識別、參數估計、模型驗證等步驟來建立模型，從而進行路基動態變形預測，利用路基變形的控制標準對路基下一級填土的時間進行預測，優化了施工組織設計，節省了時間和資金。 -
Based on the classical least squares method ( rls ) in system identification, the several new identification algorithms of parameter estimation for the autoregressive moving average ( arma ) model, are presented. they include univariable and multivariable two - stage recursive least squares - recursive extended least squares ( rls - rels ) and two - stage recursive least squares - pseudo - inverse ( rls - pi ) algorithms
本文在系統辨識經典的最小二乘法（ rls ）的基礎上，提出了自回歸滑動平均（ arma ）模型參數估計的一些新的辨識演算法，它包括單變量和多變量兩段遞推最小二乘?遞推增廣最小二乘（ rls ? rels ）演算法和兩段遞推最小二乘?偽逆（ rls ? pi ）演算法等。 -
Chapter2 : traditional time series models and multivariate fuzzy time series models. the chapter introduces the vector arma model, transfer arima model, seasonal arima, and arima model of traditional time series models, and two - factors models, heuristic models, and markov models of multivariate fuzzy time series models. i devise the process of the model construction, and propose the findings
本章介紹傳統時間數列模型（向量arma模型、 arima轉移函數模型、季節性arima模型以及arima模型）與多變量模糊時間數列三種模型?二因子模型（ two - factormodels ） 、引導式模型（ heuristicmodels ） 、馬可夫模型（ markovmodels ） ，模型建構步驟與流程，及傳統時間數列模型轉換為多變量模糊時間數列模型過程，並分別針對多變量模糊時間數列三種模型提出本研究不同於先前研究之處。 -
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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