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Bibliography

[1] Atkinson, A. C., and A. N. Donev. Optimum Experimental Designs. New York: Oxford University Press, 1992.

[2] Bates, D. M., and D. G. Watts. Nonlinear Regression Analysis and Its Applications. Hoboken, NJ: John Wiley & Sons, Inc., 1988.

[3] Belsley, D. A., E. Kuh, and R. E. Welsch. Regression Diagnostics. Hoboken, NJ: John Wiley & Sons, Inc., 1980.

[4] Berry, M. W., et al. "Algorithms and Applications for Approximate Nonnegative Matrix Factorization." Computational Statistics and Data Analysis. Vol. 52, No. 1, 2007, pp. 155–173.

[5] Bookstein, Fred L. Morphometric Tools for Landmark Data. Cambridge, UK: Cambridge University Press, 1991.

[6] Bouye, E., V. Durrleman, A. Nikeghbali, G. Riboulet, and T. Roncalli. "Copulas for Finance: A Reading Guide and Some Applications." Working Paper. Groupe de Recherche Operationnelle, Credit Lyonnais, 2000.

[7] Bowman, A. W., and A. Azzalini. Applied Smoothing Techniques for Data Analysis. New York: Oxford University Press, 1997.

[8] Box, G. E. P., and N. R. Draper. Empirical Model-Building and Response Surfaces. Hoboken, NJ: John Wiley & Sons, Inc., 1987.

[9] Box, G. E. P., W. G. Hunter, and J. S. Hunter. Statistics for Experimenters. Hoboken, NJ: Wiley-Interscience, 1978.

[10] Bratley, P., and B. L. Fox. "ALGORITHM 659 Implementing Sobol's Quasirandom Sequence Generator." ACM Transactions on Mathematical Software. Vol. 14, No. 1, 1988, pp. 88–100.

[11] Breiman, L. "Random Forests." Machine Learning. Vol. 4, 2001, pp. 5–32.

[12] Breiman, L., J. Friedman, R. Olshen, and C. Stone. Classification and Regression Trees. Boca Raton, FL: CRC Press, 1984.

[13] Breiman, L., et al., Classification and Regression Trees, Chapman & Hall, Boca Raton, 1993.

[14] Bulmer, M. G. Principles of Statistics. Mineola, NY: Dover Publications, Inc., 1979.

[15] Bury, K.. Statistical Distributions in Engineering. Cambridge, UK: Cambridge University Press, 1999.

[16] Chatterjee, S., and A. S. Hadi. "Influential Observations, High Leverage Points, and Outliers in Linear Regression." Statistical Science. Vol. 1, 1986, pp. 379–416.

[17] Collett, D. Modeling Binary Data. New York: Chapman & Hall, 2002.

[18] Conover, W. J. Practical Nonparametric Statistics. Hoboken, NJ: John Wiley & Sons, Inc., 1980.

[19] Cook, R. D., and S. Weisberg. Residuals and Influence in Regression. New York: Chapman & Hall/CRC Press, 1983.

[20] Cox, D. R., and D. Oakes. Analysis of Survival Data. London: Chapman & Hall, 1984.

[21] Davidian, M., and D. M. Giltinan. Nonlinear Models for Repeated Measurements Data. New York: Chapman & Hall, 1995.

[22] Deb, P., and M. Sefton. "The Distribution of a Lagrange Multiplier Test of Normality." Economics Letters. Vol. 51, 1996, pp. 123–130.

[23] de Jong, S. "SIMPLS: An Alternative Approach to Partial Least Squares Regression." Chemometrics and Intelligent Laboratory Systems. Vol. 18, 1993, pp. 251–263.

[24] Demidenko, E. Mixed Models: Theory and Applications. Hoboken, NJ: John Wiley & Sons, Inc., 2004.

[25] Delyon, B., M. Lavielle, and E. Moulines, Convergence of a stochastic approximation version of the EM algorithm, Annals of Statistics, 27, 94-128, 1999.

[26] Dempster, A. P., N. M. Laird, and D. B. Rubin. "Maximum Likelihood from Incomplete Data via the EM Algorithm." Journal of the Royal Statistical Society. Series B, Vol. 39, No. 1, 1977, pp. 1–37.

[27] Devroye, L. Non-Uniform Random Variate Generation. New York: Springer-Verlag, 1986.

[28] Dobson, A. J. An Introduction to Generalized Linear Models. New York: Chapman & Hall, 1990.

[29] Draper, N. R., and H. Smith. Applied Regression Analysis. Hoboken, NJ: Wiley-Interscience, 1998.

[30] Drezner, Z. "Computation of the Trivariate Normal Integral." Mathematics of Computation. Vol. 63, 1994, pp. 289–294.

[31] Drezner, Z., and G. O. Wesolowsky. "On the Computation of the Bivariate Normal Integral." Journal of Statistical Computation and Simulation. Vol. 35, 1989, pp. 101–107.

[32] DuMouchel, W. H., and F. L. O'Brien. "Integrating a Robust Option into a Multiple Regression Computing Environment." Computer Science and Statistics: Proceedings of the 21st Symposium on the Interface. Alexandria, VA: American Statistical Association, 1989.

[33] Durbin, R., S. Eddy, A. Krogh, and G. Mitchison. Biological Sequence Analysis. Cambridge, UK: Cambridge University Press, 1998.

[34] Efron, B., and R. J. Tibshirani. An Introduction to the Bootstrap. New York: Chapman & Hall, 1993.

[35] Embrechts, P., C. Klüppelberg, and T. Mikosch. Modelling Extremal Events for Insurance and Finance. New York: Springer, 1997.

[36] Evans, M., N. Hastings, and B. Peacock. Statistical Distributions. 2nd ed., Hoboken, NJ: John Wiley & Sons, Inc., 1993, pp. 50–52, 73–74, 102–105, 147, 148.

[37] Genz, A. "Numerical Computation of Rectangular Bivariate and Trivariate Normal and t Probabilities." Statistics and Computing. Vol. 14, No. 3, 2004, pp. 251–260.

[38] Genz, A., and F. Bretz. "Comparison of Methods for the Computation of Multivariate t Probabilities." Journal of Computational and Graphical Statistics. Vol. 11, No. 4, 2002, pp. 950–971.

[39] Genz, A., and F. Bretz. "Numerical Computation of Multivariate t Probabilities with Application to Power Calculation of Multiple Contrasts." Journal of Statistical Computation and Simulation. Vol. 63, 1999, pp. 361–378.

[40] Gibbons, J. D. Nonparametric Statistical Inference. New York: Marcel Dekker, 1985.

[41] Goodall, C. R. "Computation Using the QR Decomposition." Handbook in Statistics. Vol. 9, Amsterdam: Elsevier/North-Holland, 1993.

[42] Hahn, Gerald J., and S. S. Shapiro. Statistical Models in Engineering. Hoboken, NJ: John Wiley & Sons, Inc., 1994, p. 95.

[43] Hald, A. Statistical Theory with Engineering Applications. Hoboken, NJ: John Wiley & Sons, Inc., 1960.

[44] Harman, H. H. Modern Factor Analysis. 3rd Ed. Chicago: University of Chicago Press, 1976.

[45] Hastie, T., R. Tibshirani, and J. Friedman. The Elements of Statistical Learning. New York: Springer, 2001.

[46] Hochberg, Y., and A. C. Tamhane. Multiple Comparison Procedures. Hoboken, NJ: John Wiley & Sons, 1987.

[47] Hoerl, A. E., and R. W. Kennard. "Ridge Regression: Applications to Nonorthogonal Problems." Technometrics. Vol. 12, No. 1, 1970, pp. 69–82.

[48] Hoerl, A. E., and R. W. Kennard. "Ridge Regression: Biased Estimation for Nonorthogonal Problems." Technometrics. Vol. 12, No. 1, 1970, pp. 55–67.

[49] Hogg, R. V., and J. Ledolter. Engineering Statistics. New York: MacMillan, 1987.

[50] Holland, P. W., and R. E. Welsch. "Robust Regression Using Iteratively Reweighted Least-Squares." Communications in Statistics: Theory and Methods, A6, 1977, pp. 813–827.

[51] Hollander, M., and D. A. Wolfe. Nonparametric Statistical Methods. Hoboken, NJ: John Wiley & Sons, Inc., 1999.

[52] Hong, H. S., and F. J. Hickernell. "ALGORITHM 823: Implementing Scrambled Digital Sequences." ACM Transactions on Mathematical Software. Vol. 29, No. 2, 2003, pp. 95–109.

[53] Huber, P. J. Robust Statistics. Hoboken, NJ: John Wiley & Sons, Inc., 1981.

[54] Jackson, J. E. A User's Guide to Principal Components. Hoboken, NJ: John Wiley and Sons, 1991.

[55] Jain, A., and R. Dubes. Algorithms for Clustering Data. Upper Saddle River, NJ: Prentice-Hall, 1988.

[56] Jarque, C. M., and A. K. Bera. "A test for normality of observations and regression residuals." International Statistical Review. Vol. 55, No. 2, 1987, pp. 163–172.

[57] Joe, S., and F. Y. Kuo. "Remark on Algorithm 659: Implementing Sobol's Quasirandom Sequence Generator." ACM Transactions on Mathematical Software. Vol. 29, No. 1, 2003, pp. 49–57.

[58] Johnson, N., and S. Kotz. Distributions in Statistics: Continuous Univariate Distributions-2. Hoboken, NJ: John Wiley & Sons, Inc., 1970, pp. 130–148, 189–200, 201–219.

[59] Johnson, N. L., N. Balakrishnan, and S. Kotz. Continuous Multivariate Distributions. Vol. 1. Hoboken, NJ: Wiley-Interscience, 2000.

[60] Johnson, N. L., S. Kotz, and N. Balakrishnan. Continuous Univariate Distributions. Vol. 1, Hoboken, NJ: Wiley-Interscience, 1993.

[61] Johnson, N. L., S. Kotz, and N. Balakrishnan. Continuous Univariate Distributions. Vol. 2, Hoboken, NJ: Wiley-Interscience, 1994.

[62] Johnson, N. L., S. Kotz, and N. Balakrishnan. Discrete Multivariate Distributions. Hoboken, NJ: Wiley-Interscience, 1997.

[63] Johnson, N. L., S. Kotz, and A. W. Kemp. Univariate Discrete Distributions. Hoboken, NJ: Wiley-Interscience, 1993.

[64] Jolliffe, I. T. Principal Component Analysis. 2nd ed., New York: Springer-Verlag, 2002.

[65] Jöreskog, K. G. "Some Contributions to Maximum Likelihood Factor Analysis." Psychometrika. Vol. 32, 1967, pp. 443–482.

[66] Kaufman L., and P. J. Rousseeuw. Finding Groups in Data: An Introduction to Cluster Analysis. Hoboken, NJ: John Wiley & Sons, Inc., 1990.

[67] Kendall, David G. "A Survey of the Statistical Theory of Shape." Statistical Science. Vol. 4, No. 2, 1989, pp. 87–99.

[68] Kocis, L., and W. J. Whiten. "Computational Investigations of Low-Discrepancy Sequences." ACM Transactions on Mathematical Software. Vol. 23, No. 2, 1997, pp. 266–294.

[69] Kotz, S., and S. Nadarajah. Extreme Value Distributions: Theory and Applications. London: Imperial College Press, 2000.

[70] Krzanowski, W. J. Principles of Multivariate Analysis: A User's Perspective. New York: Oxford University Press, 1988.

[71] Lawless, J. F. Statistical Models and Methods for Lifetime Data. Hoboken, NJ: Wiley-Interscience, 2002.

[72] Lawley, D. N., and A. E. Maxwell. Factor Analysis as a Statistical Method. 2nd ed. New York: American Elsevier Publishing, 1971.

[73] Lilliefors, H. W. "On the Kolmogorov-Smirnov test for normality with mean and variance unknown." Journal of the American Statistical Association. Vol. 62, 1967, pp. 399–402.

[74] Lilliefors, H. W. "On the Kolmogorov-Smirnov test for the exponential distribution with mean unknown." Journal of the American Statistical Association. Vol. 64, 1969, pp. 387–389.

[75] Lindstrom, M. J., and D. M. Bates. "Nonlinear mixed-effects models for repeated measures data." Biometrics. Vol. 46, 1990, pp. 673–687.

[76] Little, Roderick J. A., and Donald B. Rubin. Statistical Analysis with Missing Data. 2nd ed., Hoboken, NJ: John Wiley & Sons, Inc., 2002.

[77] Mardia, K. V., J. T. Kent, and J. M. Bibby. Multivariate Analysis. Burlington, MA: Academic Press, 1980.

[78] Marquardt, D.W. "Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation." Technometrics. Vol. 12, No. 3, 1970, pp. 591–612.

[79] Marquardt, D. W., and R.D. Snee. "Ridge Regression in Practice." The American Statistician. Vol. 29, No. 1, 1975, pp. 3–20.

[80] Marsaglia, G., and W. W. Tsang. "A Simple Method for Generating Gamma Variables." ACM Transactions on Mathematical Software. Vol. 26, 2000, pp. 363–372.

[81] Marsaglia, G., W. Tsang, and J. Wang. "Evaluating Kolmogorov's Distribution." Journal of Statistical Software. Vol. 8, Issue 18, 2003.

[82] Martinez, W. L., and A. R. Martinez. Computational Statistics with MATLAB®. New York: Chapman & Hall/CRC Press, 2002.

[83] Massey, F. J. "The Kolmogorov-Smirnov Test for Goodness of Fit." Journal of the American Statistical Association. Vol. 46, No. 253, 1951, pp. 68–78.

[84] Matousek, J. "On the L2-Discrepancy for Anchored Boxes." Journal of Complexity. Vol. 14, No. 4, 1998, pp. 527–556.

[85] McLachlan, G., and D. Peel. Finite Mixture Models. Hoboken, NJ: John Wiley & Sons, Inc., 2000.

[86] McCullagh, P., and J. A. Nelder. Generalized Linear Models. New York: Chapman & Hall, 1990.

[87] McGill, R., J. W. Tukey, and W. A. Larsen. "Variations of Boxplots." The American Statistician. Vol. 32, No. 1, 1978, pp. 12–16.

[88] Meeker, W. Q., and L. A. Escobar. Statistical Methods for Reliability Data. Hoboken, NJ: John Wiley & Sons, Inc., 1998.

[89] Meng, Xiao-Li, and Donald B. Rubin. "Maximum Likelihood Estimation via the ECM Algorithm." Biometrika. Vol. 80, No. 2, 1993, pp. 267–278.

[90] Meyers, R. H., and D.C. Montgomery. Response Surface Methodology: Process and Product Optimization Using Designed Experiments. Hoboken, NJ: John Wiley & Sons, Inc., 1995.

[91] Miller, L. H. "Table of Percentage Points of Kolmogorov Statistics." Journal of the American Statistical Association. Vol. 51, No. 273, 1956, pp. 111–121.

[92] Milliken, G. A., and D. E. Johnson. Analysis of Messy Data, Volume 1: Designed Experiments. Boca Raton, FL: Chapman & Hall/CRC Press, 1992.

[93] Montgomery, D. Introduction to Statistical Quality Control. Hoboken, NJ: John Wiley & Sons, 1991, pp. 369–374.

[94] Montgomery, D. C. Design and Analysis of Experiments. Hoboken, NJ: John Wiley & Sons, Inc., 2001.

[95] Mood, A. M., F. A. Graybill, and D. C. Boes. Introduction to the Theory of Statistics. 3rd ed., New York: McGraw-Hill, 1974. pp. 540–541.

[96] Moore, J. Total Biochemical Oxygen Demand of Dairy Manures. Ph.D. thesis. University of Minnesota, Department of Agricultural Engineering, 1975.

[97] Mosteller, F., and J. Tukey. Data Analysis and Regression. Upper Saddle River, NJ: Addison-Wesley, 1977.

[98] Nelson, L. S. "Evaluating Overlapping Confidence Intervals." Journal of Quality Technology. Vol. 21, 1989, pp. 140–141.

[99] Patel, J. K., C. H. Kapadia, and D. B. Owen. Handbook of Statistical Distributions. New York: Marcel Dekker, 1976.

[100] Pinheiro, J. C., and D. M. Bates. "Approximations to the log-likelihood function in the nonlinear mixed-effects model." Journal of Computational and Graphical Statistics. Vol. 4, 1995, pp. 12–35.

[101] Rice, J. A. Mathematical Statistics and Data Analysis. Pacific Grove, CA: Duxbury Press, 1994.

[102] Rosipal, R., and N. Kramer. "Overview and Recent Advances in Partial Least Squares." Subspace, Latent Structure and Feature Selection: Statistical and Optimization Perspectives Workshop (SLSFS 2005), Revised Selected Papers (Lecture Notes in Computer Science 3940). Berlin, Germany: Springer-Verlag, 2006, pp. 34–51.

[103] Sachs, L. Applied Statistics: A Handbook of Techniques. New York: Springer-Verlag, 1984, p. 253.

[104] Searle, S. R., F. M. Speed, and G. A. Milliken. "Population marginal means in the linear model: an alternative to least-squares means." American Statistician. 1980, pp. 216–221.

[105] Seber, G. A. F. Linear Regression Analysis. Hoboken, NJ: Wiley-Interscience, 2003.

[106] Seber, G. A. F. Multivariate Observations. Hoboken, NJ: John Wiley & Sons, Inc., 1984.

[107] Seber, G. A. F., and C. J. Wild. Nonlinear Regression. Hoboken, NJ: Wiley-Interscience, 2003.

[108] Sexton, Joe, and A. R. Swensen. "ECM Algorithms that Converge at the Rate of EM." Biometrika. Vol. 87, No. 3, 2000, pp. 651–662.

[109] Snedecor, G. W., and W. G. Cochran. Statistical Methods. Ames, IA: Iowa State Press, 1989.

[110] Spath, H. Cluster Dissection and Analysis: Theory, FORTRAN Programs, Examples. Translated by J. Goldschmidt. New York: Halsted Press, 1985.

[111] Stein, M. "Large sample properties of simulations using latin hypercube sampling." Technometrics. Vol. 29, No. 2, 1987, pp. 143–151. Correction, Vol. 32, p. 367.

[112] Stephens, M. A. "Use of the Kolmogorov-Smirnov, Cramer-Von Mises and Related Statistics Without Extensive Tables." Journal of the Royal Statistical Society. Series B, Vol. 32, No. 1, 1970, pp. 115–122.

[113] Street, J. O., R. J. Carroll, and D. Ruppert. "A Note on Computing Robust Regression Estimates via Iteratively Reweighted Least Squares." The American Statistician. Vol. 42, 1988, pp. 152–154.

[114] Student. "On the Probable Error of the Mean." Biometrika. Vol. 6, No. 1, 1908, pp. 1–25.

[115] Vellemen, P. F., and D. C. Hoaglin. Application, Basics, and Computing of Exploratory Data Analysis. Pacific Grove, CA: Duxbury Press, 1981.

[116] Weibull, W. "A Statistical Theory of the Strength of Materials." Ingeniors Vetenskaps Akademiens Handlingar. Stockholm: Royal Swedish Institute for Engineering Research, No. 151, 1939.

[117] Zahn, C. T. "Graph-theoretical methods for detecting and describing Gestalt clusters." IEEE Transactions on Computers. Vol. C-20, Issue 1, 1971, pp. 68–86.

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