References

Aguilar, Omar, and Mike West. 2000. “Bayesian Dynamic Factor Models and Portfolio Allocation.” Journal of Business & Economic Statistics 18 (3). Taylor & Francis: 338–57.

Ahnert, Karsten, and Mario Mulansky. 2011. “Odeint—Solving Ordinary Differential Equations in C++.” arXiv 1110.3397.

Albert, J. H., and S. Chib. 1993. “Bayesian Analysis of Binary and Polychotomous Response Data.” Journal of the American Statistical Association 88: 669–79.

Barnard, John, Robert McCulloch, and Xiao-Li Meng. 2000. “Modeling Covariance Matrices in Terms of Standard Deviations and Correlations, with Application to Shrinkage.” Statistica Sinica, 1281–1311.

Betancourt, Michael. 2012. “A General Metric for Riemannian Manifold Hamiltonian Monte Carlo.” arXiv 1212.4693. http://arxiv.org/abs/1212.4693.

Betancourt, Michael, and Mark Girolami. 2013. “Hamiltonian Monte Carlo for Hierarchical Models.” arXiv 1312.0906. http://arxiv.org/abs/1312.0906.

Blei, David M., and John D. Lafferty. 2007. “A Correlated Topic Model of Science.” The Annals of Applied Statistics 1 (1): 17–37.

Blei, David M., Andrew Y. Ng, and Michael I. Jordan. 2003. “Latent Dirichlet Allocation.” Journal of Machine Learning Research 3: 993–1022.

Chung, Yeojin, Sophia Rabe-Hesketh, Vincent Dorie, Andrew Gelman, and Jingchen Liu. 2013. “A Nondegenerate Penalized Likelihood Estimator for Variance Parameters in Multilevel Models.” Psychometrika 78 (4): 685–709.

Clayton, D. G. 1992. “Models for the Analysis of Cohort and Case-Control Studies with Inaccurately Measured Exposures.” In Statistical Models for Longitudinal Studies of Exposure and Health, edited by James H. Dwyer, Manning Feinleib, Peter Lippert, and Hans Hoffmeister, 301–31. New York: Oxford University Press.

Cohen, Scott D, and Alan C Hindmarsh. 1996. “CVODE, a Stiff/Nonstiff ODE Solver in C.” Computers in Physics 10 (2): 138–43.

Cormack, R. M. 1964. “Estimates of Survival from the Sighting of Marked Animals.” Biometrika 51 (3/4): 429–38.

Curtis, S. McKay. 2010. “BUGS Code for Item Response Theory.” Journal of Statistical Software 36 (1). American Statistical Association: 1–34.

Dawid, A. P., and A. M. Skene. 1979. “Maximum Likelihood Estimation of Observer Error-Rates Using the EM Algorithm.” Journal of the Royal Statistical Society. Series C (Applied Statistics) 28 (1): 20–28.

Dempster, A. P., N. M. Laird, and D. B. Rubin. 1977. “Maximum Likelihood from Incomplete Data via the EM Algorithm.” Journal of the Royal Statistical Society. Series B (Methodological) 39 (1): 1–38.

Dormand, John R, and Peter J Prince. 1980. “A Family of Embedded Runge-Kutta Formulae.” Journal of Computational and Applied Mathematics 6 (1): 19–26.

Engle, Robert F. 1982. “Autoregressive Conditional Heteroscedasticity with Estimates of Variance of United Kingdom Inflation.” Econometrica 50: 987–1008.

Fonnesbeck, Chris, Anand Patil, David Huard, and John Salvatier. 2013. PyMC User’s Guide.

Gelman, Andrew. 2004. “Parameterization and Bayesian Modeling.” Journal of the American Statistical Association 99: 537–45.

Gelman, Andrew, J. B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin. 2013. Bayesian Data Analysis. Third. London: Chapman &Hall/CRC Press.

Gelman, Andrew, and Jennifer Hill. 2007. Data Analysis Using Regression and Multilevel-Hierarchical Models. Cambridge, United Kingdom: Cambridge University Press.

Girolami, Mark, and Ben Calderhead. 2011. “Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods.” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 73 (2): 123–214.

Greene, William H. 2011. Econometric Analysis. 7th ed. Prentice-Hall.

Hoeting, Jennifer A., David Madigan, Adrian E Raftery, and Chris T. Volinsky. 1999. “Bayesian Model Averaging: A Tutorial.” Statistical Science 14 (4): 382–417.

Hoffman, Matthew D., and Andrew Gelman. 2011. “The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo.” arXiv 1111.4246. http://arxiv.org/abs/1111.4246.

———. 2014. “The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo.” Journal of Machine Learning Research 15: 1593–1623. http://jmlr.org/papers/v15/hoffman14a.html.

Jarrett, R. G. 1979. “A Note on the Intervals Between Coal-Mining Disasters.” Biometrika 66 (1). Biometrika Trust: 191–93.

Kim, Sangjoon, Neil Shephard, and Siddhartha Chib. 1998. “Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models.” Review of Economic Studies 65: 361–93.

Lambert, Diane. 1992. “Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing.” Technometrics 34 (1).

Lewandowski, Daniel, Dorota Kurowicka, and Harry Joe. 2009. “Generating Random Correlation Matrices Based on Vines and Extended Onion Method.” Journal of Multivariate Analysis 100: 1989–2001.

Lincoln, F. C. 1930. “Calculating Waterfowl Abundance on the Basis of Banding Returns.” United States Department of Agriculture Circular 118: 1–4.

Marsaglia, George. 1972. “Choosing a Point from the Surface of a Sphere.” The Annals of Mathematical Statistics 43 (2): 645–46.

Neal, Radford M. 1996a. Bayesian Learning for Neural Networks. Lecture Notes in Statistics 118. New York: Springer.

———. 1996b. “Sampling from Multimodal Distributions Using Tempered Transitions.” Statistics and Computing 6 (4): 353–66.

———. 1997. “Monte Carlo Implementation of Gaussian Process Models for Bayesian Regression and Classification.” 9702. University of Toronto, Department of Statistics.

———. 2003. “Slice Sampling.” Annals of Statistics 31 (3): 705–67.

Papaspiliopoulos, Omiros, Gareth O. Roberts, and Martin Sköld. 2007. “A General Framework for the Parametrization of Hierarchical Models.” Statistical Science 22 (1): 59–73.

Petersen, C. G. J. 1896. “The Yearly Immigration of Young Plaice into the Limfjord from the German Sea.” Report of the Danish Biological Station 6: 5–84.

Piironen, Juho, and Aki Vehtari. 2016. “Projection Predictive Model Selection for Gaussian Processes.” In Machine Learning for Signal Processing (Mlsp), 2016 Ieee 26th International Workshop on. IEEE.

Powell, Michael J. D. 1970. “A Hybrid Method for Nonlinear Equations.” In Numerical Methods for Nonlinear Algebraic Equations, edited by P. Rabinowitz. Gordon; Breach.

Rasmussen, Carl Edward, and Christopher K. I. Williams. 2006. Gaussian Processes for Machine Learning. MIT Press.

Richardson, Sylvia, and Walter R. Gilks. 1993. “A Bayesian Approach to Measurement Error Problems in Epidemiology Using Conditional Independence Models.” American Journal of Epidemiology 138 (6): 430–42.

Rubin, Donald B. 1981. “Estimation in Parallel Randomized Experiments.” Journal of Educational Statistics 6: 377–401.

Schofield, Matthew R. 2007. “Hierarchical Capture-Recapture Models.” PhD thesis, Department of of Statistics, University of Otago, Dunedin.

Serban, Radu, and Alan C Hindmarsh. 2005. “CVODES: The Sensitivity-Enabled ODE Solver in SUNDIALS.” In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 257–69. American Society of Mechanical Engineers.

Smith, Teresa C., David J. Spiegelhalter, and Andrew Thomas. 1995. “Bayesian Approaches to Random-Effects Meta-Analysis: A Comparative Study.” Statistics in Medicine 14 (24): 2685–99.

Swendsen, Robert H., and Jian-Sheng Wang. 1986. “Replica Monte Carlo Simulation of Spin Glasses.” Physical Review Letters 57: 2607–9.

Warn, David E., S. G. Thompson, and David J. Spiegelhalter. 2002. “Bayesian Random Effects Meta-Analysis of Trials with Binary Outcomes: Methods for the Absolute Risk Difference and Relative Risk Scales.” Statistics in Medicine 21: 1601–23.

Zellner, Arnold. 1962. “An Efficient Method of Estimating Seemingly Unrelated Regression Equations and Tests for Aggregation Bias.” Journal of the American Statistical Association 57: 348–68.

Zhang, Hao. 2004. “Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics.” Journal of the American Statistical Association 99 (465). Taylor & Francis: 250–61.

Zyczkowski, K., and H.J. Sommers. 2001. “Induced Measures in the Space of Mixed Quantum States.” Journal of Physics A: Mathematical and General 34 (35). IOP Publishing: 7111.