Review/Overview Articles and Books
Luo, X., Dasgupta, T., Xie, M., & Liu, R. (2020). Leveraging the Fisher randomization test using confidence distributions: inference, combination and fusion learning. Journal of the Royal Statistical Society: Series B (in press).
Shafer, G., & Vovk, V. (2019). Game-Theoretic Foundations for Probability and Finance (Vol. 455). John Wiley & Sons.
Schweder, T., & Hjort, N. L. (2016). Confidence, likelihood, probability (Vol. 41). Cambridge University Press.
Efron, B., & , Hastie, T. (2016). Computer Age Statistical Inference. Cambridge University Press.
Hannig, J., Iyer, H., Lai, R. C., & Lee, T. C. (2016). Generalized fiducial inference: A review and new results. Journal of the American Statistical Association, 111(515), 1346-1361.
Liu, K., & Meng, X. L. (2016). There is individualized treatment. Why not individualized inference?. Annual Review of Statistics and Its Application, 3, 79-111.
Reid, N., & Cox, D. R. (2015). On some principles of statistical inference. International Statistical Review, 83(2), 293-308.
Martin, R., & Liu, C. (2015). Inferential models: reasoning with uncertainty. Chapman and Hall/CRC.
Balasubramanian, V., Ho, S. S., & Vovk, V. (Eds.). (2014). Conformal prediction for reliable machine learning: theory, adaptations and applications. Newnes.
Berger, J. O. (2013). Statistical decision theory and Bayesian analysis. Springer Science & Business Media.
Xie, M. G., & Singh, K. (2013). Confidence distribution, the frequentist distribution estimator of a parameter: A review. International Statistical Review, 81(1), 3-39. [Dicussion and Rejoinder]
Robert, C. (2007). The Bayesian choice: from decision-theoretic foundations to computational implementation. Springer Science & Business Media.