최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기응용통계연구 = The Korean journal of applied statistics, v.33 no.1, 2020년, pp.47 - 59
심보현 (부산대학교 통계학과) , 정윤식 (부산대학교 통계학과)
In this paper, we present the longitudinal Markov binary regression model with t-link function when its transition order is known or unknown. It is assumed that logit or probit models are considered in binary regression models. Here, t-link function can be used for more flexibility instead of the pr...
Albert, J. H. and Chib, S. (1993). Bayesian analysis of binary and Polychotomous response data, Journal of the American Statistical Association, 88, 669-679.
Azzalini, A. (1982). Approximate filtering of parameter driven processes, Journal of Time Series Analysis, 3, 219-223.
Bartholomew, D. J. (1983). Some recent developments in social statistics, International Statistical Review, 51, 1-9.
Brooks, S. P. and Gelman, A. (1997). General methods for monitoring convergence of iterative simulations, Journal of Computational and Graphical Statistics, 7, 434-455.
Cox, D. R. (1970). The Analysis of Binary Data, Methuen, London.
Cox, D. R. (1981). Statistical analysis of time series: some recent developments, Scandinavian Journal of Statistics, 8, 93-115.
Erkanli, A., Soyer R., and Angold A. (2001). Bayesian analyses of longitudinal binary data using Markov regression models of unknown order, Statistics in Medicine, 20, 755-770.
Fisher, R. A. (1925). Applications of " Student's" distribution, Metron, 5, 90-104.
Gelman, A. and Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences, Statistical Science, 7, 457-511.
George, E. I. and McCulloch, R. E. (1993). Variable selection via Gibbs sampling, Journal of the American Statistical Association, 88, 881-889.
George, E. I. and McCulloch, R. E. (1997). Approaches for Bayesian variable selection, Statistica Sinica, 7, 339-373.
Gosset, W. S. (1908). The probable error of a mean, Biometrika, 6, 1-25.
Green, P. J. (1995). Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrika, 82, 711-732.
Kalbfleisch, J. D. and Lawless, J. F. (1985). The analysis of panel data under a Markov assumption, Journal of the American Statistical Association, 80, 863-871.
Korn, E. L. and Whittemore, A. S. (1979). Methods for analyzing panel studies of acute health effects of air pollution, Biometrics, 35, 795-802.
Kuo, L. and Mallick, B. (1998). Variable selection for regression models, Sankhya: The Indian Journal of Statistics, B 60, 65-81.
Lee, T. C., Judge, G. G., and Zellner, A. (1968). Maximum likelihood and Bayesian estimation of transition probabilities, Journal of the American Statistical Association, 63, 1162-1179.
Lee, T. C., Judge, G. G., and Zellner, A. (1970). Estimating the Parameters of the Markov Probability Model from Aggregate Time Series Data, North-Holland and Pub. Co., Amsterdam.
Meshkani, M. (1978). Empirical Bayes estimation of transition probabilities for Markov chains (Ph.D. Dissertation), Florida State University.
Singer, B. and Spilerman, S. (1976a). The Representation of Social Processes by Markov Models, American Journal of Sociology, 82, 1-54.
Singer, B. and Spilerman, S. (1976b). Some Methodological Issues in the Analysis of Longitudinal Surveys, Annals of Economic and Sociological Measurement, 5, 447-474.
Sommer, A., Katz, J. and Tarwotjo, I. (1984). Increased risk of respiratory infection and diarrhea in children with pre-existing mild vitamin A deficiency, American Journal of Clinical Nutrition, 40, 1090-1095.
Spiegelhalter, D. A., Best, N. G., Carlin, B. P., and Linde, A. V. (2002). Bayesian measures of model complexity and fit, Journal of the Royal Statistical Society: Series B, 64, 583-639.
Tanner, T. A. and Wong, W. H. (1987). The calculation of posterior distributions by data augmentation, Journal of the American Statistical Association, 82, 528-549.
Wasserman, S. (1980). Analyzing social networks as stochastic processes, Journal of the American Statistical Association, 75, 280-294.
Zeger, S. L. and Qaqish, B. (1988). Markov regression models for time series: a quasi-likelihood approach, Biometrics, 44, 1019-1031.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
오픈액세스 학술지에 출판된 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.