本論文探討動態受限因子模型在高維度時間序列資料上的應用。在模式設定上，有別於藉由主觀訊息預先設定受限矩陣，本研究將sparse fused lasso的技巧引入最大概似估計式中，透過參數估計並搭配集群分析與群數選取指標，利用資料訊息決定模式中受限矩陣的結構，以達到簡化高維度時間序列建模的目的。模擬研究顯示所提出之方法，在簡化模式結構上頗具成效，此方法已成功地運用在財務相關之實例分析。

Calinski, T. and J. Harabasz (1974). A dendrite method for cluster analysis. Communications in Statistics. 3, 1-27.
Dempster, A. P., N. M. Laird and D. B. Rubin (1977). Maximum likelihood from incomplete data via em algorithm. Journal of the Royal Statistical Society Series B-Methodological 39(1),1-38.
Forni, M., M. Hallin, M. Lippi and L. Reichlin (2000). The generalized dynamic-factor model: Identification and estimation.. Review of Economics and Statistics 82(4), 540-554.
Geweke, J. (1977). The Dynamic Factor Analysis of Economic Time Series.
Guo, J. A., G. James, E. Levina, G. Michailidis and J. Zhu (2010). Principal component analysis with sparse fused loadings. Journal of Computational and Graphical Statistics 19(4), 930-946.
Hartigan, J. A. (1975). Clustering Algorithms. Wiley.
Krzanowski, W. J. and Y. T. Lai (1988). A criterion for determining the number of groups in a data set using sum-of-squares clustering. Biometrics 44(1), 23-34.
R. E. Kalman. (1960). A new approach to linear filtering and prediction problems, transaction of the asme, Journal of Basic Engineering, 35-45.
Sargent, T. J. and C. A. Sims (1977). Business cycle modeling without pretending to have too much a-priori economic theory, New Methods in Business Cycle Research.
Stock, J. H. and M. W. Watson (1998). Diffusion indexes. NBER Working Paper No.6702.
Stock, J. H. and M. W. Watson (2002). Macroeconomic forecasting using diffusion indexes. Journal of Business & Economic Statistics 20(2), 147-162.
Tsai, H. and R. S. Tsay (2010). Constrained factor models Journal of the American Statistical Association 105(492), 1593-1605.
Watson, M. W. and R. F. Engle (1983). Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression-models. Journal of Econometrics 23(3), 385-400.