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Auxiliary mixture sampling with applications to logistic models

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  • Fruhwirth-Schnatter, Sylvia
  • Fruhwirth, Rudolf

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  • Fruhwirth-Schnatter, Sylvia & Fruhwirth, Rudolf, 2007. "Auxiliary mixture sampling with applications to logistic models," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3509-3528, April.
  • Handle: RePEc:eee:csdana:v:51:y:2007:i:7:p:3509-3528
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    References listed on IDEAS

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    1. Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004. "Stochastic Volatility with Leverage: Fast Likelihood Inference," CIRJE F-Series CIRJE-F-297, CIRJE, Faculty of Economics, University of Tokyo.
    2. Zellner, Arnold & Rossi, Peter E., 1984. "Bayesian analysis of dichotomous quantal response models," Journal of Econometrics, Elsevier, vol. 25(3), pages 365-393, July.
    3. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 361-393.
    4. McCulloch, Robert E. & Polson, Nicholas G. & Rossi, Peter E., 2000. "A Bayesian analysis of the multinomial probit model with fully identified parameters," Journal of Econometrics, Elsevier, vol. 99(1), pages 173-193, November.
    5. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
    6. Weber, Andrea, 2002. "State Dependence and Wage Dynamics: A Heterogeneous Markov Chain Model for Wage Mobility in Austria," Economics Series 114, Institute for Advanced Studies.
    7. John F. Geweke & Michael P. Keane, 1997. "Mixture of normals probit models," Staff Report 237, Federal Reserve Bank of Minneapolis.
    8. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
    9. Chib, Siddhartha & Greenberg, Edward & Winkelmann, Rainer, 1998. "Posterior simulation and Bayes factors in panel count data models," Journal of Econometrics, Elsevier, vol. 86(1), pages 33-54, June.
    10. Carter, C.K. & Kohn, R., "undated". "Semiparametric Bayesian inference for time series with mixed spectra," Statistics Working Paper _005, Australian Graduate School of Management.
    11. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.
    12. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    13. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
    14. Fruhwirth-Schnatter, Sylvia & Tuchler, Regina & Otter, Thomas, 2004. "Bayesian Analysis of the Heterogeneity Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 2-15, January.
    15. Peter Lenk & Wayne DeSarbo, 2000. "Bayesian inference for finite mixtures of generalized linear models with random effects," Psychometrika, Springer;The Psychometric Society, vol. 65(1), pages 93-119, March.
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    Cited by:

    1. Steven Scott, 2011. "Data augmentation, frequentist estimation, and the Bayesian analysis of multinomial logit models," Statistical Papers, Springer, vol. 52(1), pages 87-109, February.
    2. Sylvia Frühwirth‐Schnatter & Christoph Pamminger & Andrea Weber & Rudolf Winter‐Ebmer, 2012. "Labor market entry and earnings dynamics: Bayesian inference using mixtures‐of‐experts Markov chain clustering," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(7), pages 1116-1137, November.
    3. Omori, Yasuhiro & Watanabe, Toshiaki, 2008. "Block sampler and posterior mode estimation for asymmetric stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2892-2910, February.
    4. Sylvia Kaufmann, 2011. "K-state switching models with endogenous transition distributions," Working Papers 2011-13, Swiss National Bank.
    5. Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2010. "Stochastic model specification search for Gaussian and partial non-Gaussian state space models," Journal of Econometrics, Elsevier, vol. 154(1), pages 85-100, January.
    6. Nakajima, Jouchi & Kunihama, Tsuyoshi & Omori, Yasuhiro & Frühwirth-Schnatter, Sylvia, 2012. "Generalized extreme value distribution with time-dependence using the AR and MA models in state space form," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3241-3259.
    7. Aßmann, Christian & Boysen-Hogrefe, Jens, 2011. "A Bayesian approach to model-based clustering for binary panel probit models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 261-279, January.
    8. Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2008. "Marginal likelihoods for non-Gaussian models using auxiliary mixture sampling," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4608-4624, June.
    9. Wagner, Helga & Tüchler, Regina, 2010. "Bayesian estimation of random effects models for multivariate responses of mixed data," Computational Statistics & Data Analysis, Elsevier, vol. 54(5), pages 1206-1218, May.
    10. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    11. Sylvia Frühwirth-Schnatter & Christoph Pamminger, 2009. "Bayesian Clustering of Categorical Time Series Using Finite Mixtures of Markov Chain Models," NRN working papers 2009-07, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.

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