References 1 Schmitz, T., and Smith, K. S., 2009, Machining Dynamics: Frequency Response to Improved Productivity, Springer, New York.

2 Kumanchik, L., and Schmitz, T., 2007, “Improved Analytical Chip Thickness Model for Milling,” Precis. Eng., 31, pp. 317–324. [CrossRef]

3 Andrieu, C., de Freitas, N., Doucet, A., and Jordan, M., 2003, “An Introduction to MCMC for Machine Learning,” Mach. Learn., 50, pp. 5–43. [CrossRef]

4 Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., and Teller, E., 1953, “Equations of State Calculations by Fast Computing Machines,” J. Chem. Phys., 21(6), pp. 1087–1092.[CrossRef]

5 Hastings, W. K., 1970, “Monte Carlo Sampling Methods Using Markov Chains and Their Applications,” Biometrika, 57, pp. 97–109. [CrossRef]

6 Roberts, G. O., Gelman, A., and Gilks, W. R., 1997, “Weak Convergence and Optimal Scaling of Random Walk Metropolis Algorithms,” Ann. Appl. Probab., 7(1), pp. 110–112. [CrossRef]

7 Chib, S., and Greenberg, E., 1995, “Understanding the Metropolis Hastings Algorithm,” The Am. Stat., 49(4), pp. 327–335.

8 Gelfand, A., and Smith, A., 1990, “Sampling-Based Approaches to Calculating Marginal Densities,” J. Am. Stat. Assoc., 85(410), pp. 398–409. [CrossRef]

9 Duncan, G. S., Kurdi, M., Schmitz, T., and Snyder, J., 2006, “Uncertainty Propagation for Selected Analytical Milling Stability Limit Analyses,” Trans. NAMRI/SME, 34, pp. 17–24. Available at:http://plaza.ufl.edu/mhkurdi/namrc.pdf