Andrews, Donald W. K., 1997. ``A simple counterexample to the bootstrap''. Cowles Foundation for Research in Economics, Yale University.
Bates, Douglas M. and Watts, Donald G., 1988. Nonlinear Regression Analysis and Its Applications. New York: John Wiley & Sons.
Browne, Michael W. and Arminger, Gerhard, 1995. ``Specification and estimation of mean- and covariance-structure models'', in Handbook of Statistical Modeling for the Social and Behavioral Sciences, Gerhard Arminger, Clifford C. Clogg, and Michael E. Sobel (eds.), New York: Plenum.
Cox, D.R., and Hinkley, D.V., 1974. Theoretical Statistics. London: Chapman and Hall.
Cook, R.D., and Weisberg, S., 1990. ``Confidence Curves in Nonlinear Regression'', Journal of the American Statistical Association, 85:544-551.
Meeker, W.Q., and L. A. Escobar, 1995. ``Teaching about approximate confidence regions based on maximum likelihood estimation'', The American Statistician, 49:48-53.
Dennis, Jr., J.E., and Schnabel, R.B., 1983. Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Englewood Cliffs, NJ: Prentice-Hall.
Efron, Gradley, Robert J. Tibshirani, 1993. An Introduction to the Bootstrap. New York: Chapman & Hall.
Fletcher, R., 1987. Practical Methods of Optimization. New York: Wiley.
Gallant, A.R., 1987. Nonlinear Statistical Models. New York: Wiley.
Geweke, John, 1995. ``Posterior Simulators in Econometrics'', Working Paper 555, Research Department, Federal Reserve Bank of Minneapolis.
Gill, P. E. and Murray, W. 1972. ``Quasi-Newton methods for unconstrained optimization.'' J. Inst. Math. Appl., 9, 91-108.
Gourieroux, Christian, Holly, Alberto, and Monfort, Alain, 1982. ``Likelihood ratio test, Wald Test, and Kuhn-Tucker test in linear models with inequality constraints on the regression parameters'', Econometrica, 50:63-80.
Han, S.P., 1977. ``A globally convergent method for nonlinear programming.'' Journal of Optimization Theory and Applications, 22:297-309.
Hartmann, Wolfgang M. and Hartwig, Robert E., 1995. ``Computing the Moore-Penrose inverse for the covariance matrix in constrained nonlinear estimation'', SAS Institute, Inc., Cary, NC.
Hock, Willi and Schittkowski, Klaus, 1981. Lecture Notes in Economics and Mathematical Systems. New York: Springer-Verlag.
Jamshidian, Mortaza and Bentler, P.M., 1993. ``A modified Newton method for constrained estimation in covariance structure analysis.'' Computational Statistics & Data Analysis, 15:133-146.
Newton, M.A. and Raftery, A.E., 1994. ``Approximate Bayesian inference with the weighted likelihood bootstrap'', J.R. Statist. Soc. B, 56:3-48.
O'Leary, Dianne P., and Rust, Bert W., 1986. ``Confidence intervals for inequality-constrained least squares problems, with applications to ill-posed problems''. American Journal for Scientific and Statistical Computing, 7(2):473-489.
Rubin, D.B., 1988. ``Using the SIR algorithm to simulate posterior distributions'', in Bayesian Statistics 3, J.M. Bernardo, M.H. DeGroot, D.V. Lindley, and A.F.M. Smith (eds.), pp. 395-402.
Rust, Bert W., and Burrus, Walter R., 1972. Mathematical Programming and the Numerical Solution of Linear Equations. New York: American Elsevier.
Schoenberg, Ronald, 1995. CML Users Guide. Maple Valley, WA, USA: Aptech Systems, Inc.
Self, Steven G. and Liang, Kung-Yee, 1987. ``Asymptotic properties of maximum lieklihood estimators and likelihood ratio tests under nonstandard conditions'', Journal of the American Statistical Association, 82:605-610.
Terrell, G.R., 1990. ``The maximal smoothing principle in density estimation'', Journal of the American Statistical Association, 85: 470-477.
Wolak, Frank, 1991. ``The local nature of hypothesis tests involving inequality constraints in nonlinear models'', Econometrica, 59:981-995.