References

  • Bassett, G. W. and Koenker, R. (1982), “An Empirical Quantile Function for Linear Models with iid Errors,” Journal of the American Statistical Association, 77, 401–415.

  • Bishop, Y. M. M., Fienberg, S. E., and Holland, P. W. (1975), Discrete Multivariate Analysis: Theory and Practice, Cambridge, MA: MIT Press.

  • Charnes, A., Frome, E. L., and Yu, P. L. (1976), “The Equivalence of Generalized Least Squares and Maximum Likelihood Estimation in the Exponential Family,” Journal of the American Statistical Association, 71, 169–172.

  • Cox, D. R. (1970), Analysis of Binary Data, London: Metheun.

  • Cox, D. R. and Snell, E. J. (1989), The Analysis of Binary Data, 2nd Edition, London: Chapman & Hall.

  • Grizzle, J. E., Starmer, C. F., and Koch, G. G. (1969), “Analysis of Categorical Data by Linear Models,” Biometrics, 25, 489–504.

  • Hadley, G. (1962), Linear Programming, Reading, MA: Addison-Wesley.

  • Hartley, H. O. (1961), “The Modified Gauss-Newton Method for the Fitting of Non-linear Regression Functions by Least Squares,” Technometrics, 3, 269–280.

  • Jennrich, R. I. and Moore, R. H. (1975), “Maximum Likelihood Estimation by Means of Nonlinear Least Squares,” American Statistical Association, 1975 Proceedings of the Statistical Computing Section, 57–65.

  • Kaiser, H. F. and Caffrey, J. (1965), “Alpha Factor Analysis,” Psychometrika, 30, 1–14.

  • Kastenbaum, M. A. and Lamphiear, D. E. (1959), “Calculation of Chi-Square to Test the No Three-Factor Interaction Hypothesis,” Biometrics, 15, 107–122.

  • Koenker, R. and Bassett, G. W. (1978), “Regression Quantiles,” Econometrica, 46, 33–50.

  • Madsen, K. and Nielsen, H. B. (1993), “A Finite Smoothing Algorithm for Linear $L_1$ Estimation,” SIAM Journal on Optimization, 3, 223–235.

  • Nelder, J. A. and Wedderburn, R. W. M. (1972), “Generalized Linear Models,” Journal of the Royal Statistical Society, Series A, 135, 370–384.