參考文獻 |
[1] Carter, C. K., Kohn, R. (1994) Markov chain Monte Carlo in conditionally
Gaussian state space models. Biometrika, 83, 589-601.
[2] Darsow, W. F., Nguten, B., Olsen, E. T. (1992) Copulas and Markov Processes.
IllinoisJournalofMathematics; 36; 600 ?? 642.
[3] Dempster, A.P.; Laird, N.M.; Rubin, D.B. (1977). Maximum Likelihood from
Incomplete Data via the EM Algorithm. Journal of the Royal Statistical
Society.Series B (Methodological) 39(1): 1{38.
[4] Domma, F., Giordano, S., Francesco, P. P. (2009). Statistical modeling of temporal
dependence in nancial data via a copula function. Communications in
Statistics-Simulation and Computation 38:703{728.
[5] Emura, T. Long, T. H., Sun, L. H. (2017) R routines performing estimation and statistical
process control under copula-based time series models. Communications
in Statistics Simulation and Computation, 46(4), 3067-3087.
[6] Frees, E. W., Valadez, E. (1998) Understanding the relationships using copulas.
North American Actuarial Journal, 2, 1-25.
[7] Gelman, A., Rubin, D. (1992) Inference from Iterative simulation using Multiple
sequences. Statistical Science, 7, 457-473.
[8] Kim JM, Hwang SY (2017). Directional dependence via Gaussian copula beta
regression model with asymmetric GARCH marginals. Communications in
Statistics-Simulation and Computation, 46(10), 7639-7653.
[9] Kim JM, Baik J (2018a), Anomaly detection in sensor data, The Korean Reliability
Society, Journal of Applied Reliability 18(1): 20-32.
[10] Kim JM, Baik J (2018b), Change point detection by copula conditional distributions,
manuscript.
47
[11] Joe,H.(1997) Multivariate Models and dependence. Chapman & hall.
[12] Long, T. H., Emura, T. (2014) A control chart using copula-based Markov chain
models. Journal of the Chinese Statistical Association , 52(4), 466-496.
[13] Ly, A., Marsman, M., Verhagen, A., Grasman, R., &Wagenmakers, E.-J. (2015).
A tutorial on Fisher information. Journal of Mathematical Psychology, (submitted
for publication).
[14] M. Kok, J. Dahlin, T. B. Schon, A. Wills, Newton-based maximum likelihood
estimation in nonlinear state space models, Proc. 17th IFAC Symp. Syst.
Identificat., pp. 969-974, Oct. 2015.
[15] Nelsen, R. B. (2006) An Introduction to Copulas, 2nd Edition. Springer Series
in Statistics, Springer-V erlag : NewY ork.
[16] P. Zangari, An improved methodology for measuring VaR, Risk Metrics Monitor,
2nd quarter, Reuters/J.P. Morgan, 7{25 (1996).
[17] R development Core Team (2014) R: a language and environment for statistical
computing. Foundation for Statistical Computing, R version 3:2:1.
[18] Ross, S. M. (2006) Simulation,4th Edition. Elevier. |