跳到主要內容

臺灣博碩士論文加值系統

(44.192.20.240) 您好!臺灣時間:2024/03/04 11:47
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:葉怡娟
研究生(外文):Yi-Chuan Yeh
論文名稱:具多變量t自相關誤差的時間數列迴歸模型
論文名稱(外文):Bayesian inference for time series regression models with multivariate t autoregressions on errors
指導教授:李昭勝林宗儀林宗儀引用關係
指導教授(外文):Jack C. LeeTsung I. Lin
學位類別:碩士
校院名稱:國立交通大學
系所名稱:統計學研究所
學門:數學及統計學門
學類:統計學類
論文種類:學術論文
論文出版年:2006
畢業學年度:94
語文別:英文
論文頁數:39
中文關鍵詞:近似推論蒙地卡羅馬可夫鏈預測分配再參數化
外文關鍵詞:Approximate inferenceMarkov chain Monte CarloPredictive distributionReparameterization
相關次數:
  • 被引用被引用:0
  • 點閱點閱:158
  • 評分評分:
  • 下載下載:23
  • 收藏至我的研究室書目清單書目收藏:0
本篇論文考慮具自迴歸多變量t誤差的線性迴歸模型的貝氏方法,它的條件變異數滿足了GARCH模型的一種型式。在沒有訊息的先驗分配下,我們提出了近似貝氏的後驗方法與預測的推論。我們也運用馬可夫鏈蒙地卡羅去更精確地計算後驗分配。為提高計算上的效率,我們提供了一個求具AR(p)過程的自相關矩陣之反矩陣的快速計算方法。最後我們用一個美國利率的實例來闡述我們所提出的方法。
This thesis considers a Bayesian approach to the regression model with autoregressive multivariate t errors, whose conditional variance satis‾es a kind of generalized autoregressive conditional heteroscedastic model. We present
the approximate Bayesian posterior and predictive inferences under a non-informative prior. Markov chain Monte Carlo computational schemes are developed for precisely accounting for the posterior uncertainties. To enhance the computational e±ciency, we provide a fast method to compute the inverse autocorrelation matrix of an AR(p) process. A real example of the U.S. interest rates is conducted to demonstrate our methodologies.
Contents
1. Introduction .................................3
2. Approximate Bayesian inference .............. 4
2.1. The model ....................................4
2.2. Posterior inference ......................... 7
2.3. Predictive inference ....................... .9
3. Markov chain Monte Carlo inference ......... 11
3.1. Implementation ..............................11
3.2. Forecasting future values and volatilities...12
4. An application: the U.S. interest rates......13
5. Discussion ..................................21
References
Anderson, T.W. (2003), An Introduction to Multivariate Statistical Analysis (Wiley, 3rd. ed.).
Arellano-Valle, R.B., Galea-Rojas, M., Zuazola P.I. (2000), Bayesian sensitivity analysis in elliptical linear regression models. J Statist. Plan. Inference 86, 175-199.
Barndor®-Nielsen, O. E., Schou, G. (1973), On the reparameterisation of autoregressive models by partial autocorrelations. J. Multivariate. Anal. 3, 408-419.
Bollerslev, T. (1986), Generalized autoregressive conditional heteroscedasticity. J. Econometrics 31, 307-27.
Box, G.E.P., Jenkins, G.M., Reinsel, G.C. (1994), Time Series Analysis Forecasting and Control (Holden-Day, San Francisco, 3rd ed.).
Brooks, S. P. and Gelman, A. (1998), General methods for monitoring convergence of iterative simulations. J. Comp. Graph. Statist. 7, 434-455.
Chen, C.W.S., Lee, J.C., Lee, S.Y., Niu, W.F. (2004), Bayesian estimation for time series regressions improved with exact likelihoods, J. Statist. Comput. Simulation 74, 727 - 740.
Chib, S. (1993), Bayes regression with autoregressive errors: A Gibbs sampling approach. J. Econometrics. 58, 275-294.
Chib, S., Osiewalski, J., Steel M.F.J. (1991), Posterior inference on degrees of freedom parameters in multivariate-t regression models. Econom Lett. 37, 391-397.
Chib, S., Tiwari, R.C., JAMMLAMADAKA (1988), Bayes prediction in regression with elliptical errors. J. Econometrics. 38, 349-360.
Engle, R.F. (1982), Autoregressive conditional heteroscedasticity with estimates of variance of United Kingdom in°ation. Econometrica 50, 987-1007.
Gelman, A., Carlin, J.B., Stern, H.S., Rubin, D.B. (2004). Bayesian Data Analysis (Chapman & Hall, New York, 2nd ed.)
Kim, H.M., Mallick B.K. (2003), A note on Bayesian spatial prediction using the elliptical distribution. Statist. Probab. Lett. 64, 271-276.
Ljung, G.M., Box, G.E.P. (1980), Analysis of variance with autocorrelated obser-vations. Scand. J. Statist. 7, 172-180.
Monahan, J.F. (1984), A note on enforcing stationarity in autoregressive moving average models. Biometrika 71, 403-404.
Lee, J.C.,Wang, R.S., Lin, T.I. (2004), On the inverse of the autocorrelation matrix for an AR(p) process. J. Chinese Statist. Assoc. 42, 81-89.
McCulloch, R.E., Tsay R.S. (1994), Bayesian analysis of autoregressive time series via the Gibbs sampler. J. Time Ser. Anal. 15, 235-250.
Osiewalski, J. (1991), A note on Bayesian inference in a regression model with elliptical errors. J. Econometrics 48, 183-193.
Osiewalski, J., Steel M.F.J. (1993), Robust Bayesian inference in elliptical models. J. Econometrics 57, 345-363.
Singh, R.S. (1988), Estimation of error variance in linear regression models with errors having multivariate student-t distribution with unknown degrees of free-dom. Econom Lett. 27, 47-53.
Tarami, B., Pourahmadi M. (2003), Multi-variate t autoregressions: innovations, prediction variances and exact likelihood equation. J. Time Ser. Anal. 24, 739-754.
Zellner, A. (1976), Bayesian and non-Bayesian analysis of the regression model with multivariate student-t error terms. J. Amer. Statist. Assoc. 71, 400-405.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top