本文的主要目的是以貝氏推論結合Gibbs-sampling抽樣法估計Kuan et al.(2005)所提出的IRS模型，不同於Kuan et al.(2005)文中以準最大概似估計法(QMLE)推估參數的作法，本文研究方法將具有幾項特點。首先在貝氏推論下，研究者對於參數設定的主觀想法將反應於參數的先驗分配中，其次透過Gibbs-sampling抽樣法，將可避免準最大概似估計法直接計算概似函數的步驟，大大降低了複雜的計算過程。其三，相較於採取準最大概似估計法估計模型參數，Gibbs-sampling抽樣法為approximation-free，它由完全條件分配在每一期的抽樣過程取得一組參數值，重複抽樣過程多次後將所得參數值予以平均求得參數估計值。

由於Gibbs-sampling抽樣法下假設參數為一未知的分配，而不是一個未知的常數，所以由完全條件分配估計參數的作法將包含更多的資訊。

本文推導了Gibbs-sampling抽樣法估計IRS模型的詳細步驟，只要我們掌握Gibbs-sampling流程中所需的完全條件分配，便可由流程中產生一連串關於參數分配的實現值，當這些實現值的抽樣過程符合文中Gibbs-sampling所要求的性質時，便可視為從真實母體中所抽出的樣本，如此便可透過這些樣本了解母體分配的特性。

徐士勳(2000)景氣波動之計量分析國立台灣大學經濟研究所碩士論文
Carlin, B. P., Poloson, N.G.and Stoffer, D.S. (1992). A Monte Carlo approach to nonnormal and nonlinear state space modeling,Journal of the American Statistical Association 87, 493--500.
Carter, C.K.and P. Kohn~(1994). On Gibbs Sampling for State Space Models,Biometrika,81, 541--553.
Chung-Ming Kuan, Yu-Lieh Huang,and Ruey S. Tsay(2005). An Unobersved-Component Model with Switching Permanent and Transitory Innovations, Journal of Business and Economic Statistics,23,, 443--454.
Elwood, S.K. (1998). Is the persistence of shocks to output asymmetric ? Journal of Monetary Economics,41, 411--426.
Hamilton, J. D.(1994). Time Series Analysis Princeton, NJ: Princeton University Press.
Harvey, A.C. (1989). Forecasting, structural time series models and the Kalman filter,Cambridge University press.
Huang, Y.L. (2006), Gibbs Sampling for an Innovation Regime-Switching Model,working paper.
James, H. Albert~and Siddhartha Chibs(1993). Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts,Journal of Business and Economic Statistics,11, 1-15.
Kim, C. J.and C. R.Nelson (1998).Business Cycle Turning Points, a New Coincident Index, and Tests of Duration Dependence Based on a Dynamic Factor Model with Regime-Switching,Review of Economics and Statistics,80, 188-201.
Kim, C. J.~and C. R. Nelson(1999).State-Space Models with Regime Switching,Classical and Gibbs Sampling Approaches with Applications,Cambridge, MA: MIT Press.
Liu, J., Wong, W. H.and Kong, A. (1994).Covariance structure of the Gibbs sampler with applications to the comparison of estimators and augmentation schemes.Biometrika,81,, 27--40.