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Siddhartha Chib is an econometrician and statistician, the Harry C. Hartkopf Professor of Econometrics and Statistics at Washington University in St. Louis. His work is primarily in Bayesian statistics, econometrics, and Markov chain Monte Carlo methods .
Professor Chib is an econometrician and statistician who works in Bayesian statistics, econometrics and Markov chain Monte Carlo (MCMC) methods. He is a Fellow of the American Statistical Association, of the International Society of Bayesian Analysis and the Journal of Econometrics.
Siddhartha Chib. Professor Chib's research is in the area of Bayesian statistics and Markov chain Monte Carlo computational methods. He has published papers on a number of different topics including the analysis of binary and ordinal data, Markov mixture models, stochastic volatility, Metropolis-Hastings algorithms and model choice.
Bayesian analysis of binary and polychotomous response data. JH Albert, S Chib. Journal of the American statistical Association 88 (422), 669-679. , 1993. 4288. 1993. Stochastic volatility: likelihood inference and comparison with ARCH models. S Kim, N Shephard, S Chib. The review of economic studies 65 (3), 361-393.
Siddhartha Chib and Edward Greenberg extended this idea and also proposed simulation-based inference methods for the multivariate probit model which simplified and generalized parameter estimation.
Siddhartha Chib is an econometrician and statistician, the Harry C. Hartkopf Professor of Econometrics and Statistics at Washington University in St. Louis. His work is primarily in Bayesian statistics, econometrics, and Markov chain Monte Carlo methods.
Siddhartha Chib, Yasuhiro Omori and Manabu Asai Abstract We provide a detailed summary of the large and vibrantemerging literature that deals with the multivariate modeling of conditional volatility of financial time series within the framework of stochastic volatility. The developments and achievements in this area represent one of the great suc-
