Bibliography

1

Wahba, G. (1989) Spline Models in Statistics SIAM Regional Conference Series in Applied Mathematics.

2

Wahba, G. (1975) ``A Completely Automatic French Curve: Fitting Spline Functions by Cross-Validation'' Communications in Statistics 4 1-17.

3

Friedman, J.H. (1991) ``Multivariate Adaptive Regression Splines'' Annals of Statistics 19-1 1-141.

4

Cox, D.D. (1983) ``Asymptotics for M-type Smoothing Splines'' Annals of Statistics 11-2 530-551.

5

Cox, D.D. (1984) ``Multivariate Smoothing Spline Functions'' SIAM Journal of Numerical Analysis 21-4 789-813.

6

Eubank, R.L. (1988) Spline Smoothing and Nonparametric Regression New York, Marcel Dekker.

Nonparametric Estimation via Sieves, Series, Neural Nets other ``Flexible Functional Forms''

7

Grenander, U. (1981) Abstract Inference Wiley.

8

Geman, S. and C. Hwang (1982) ``Nonparametric Maximum Likelihood Estimation by the Method of Sieves'' Annals of Statistics 10 401-414.

9

Severini, T.A. and W.H. Wong (1987) ``On Maximum Likelihood Estimation in Infinite-Dimensional Parameter Spaces'' Annals of Statistics 19 603-632.

10

Shen, X. and W.H. Wong (1994) ``Convergence Rates for Sieve Estimates'' Annals of Statistics 22 580-615.

11

White, H. and Wooldridge, J.A. (1991) ``Some Results on Sieve Estimators with Dependent Observations'' in W.A. Barnett, J.L. Powell, G. Tauchen (eds.) Nonparametric and Semiparametric Methods in Econometrics and Statistics. Cambridge University Press.

12

Gallant, A.R. (1987) ``Identification and Consistency in Seminonparametric Regression'' in T. Bewley (ed.) Advances in Econometrics Proceedings of the 5th World Congress of the Econometric Society, Cambridge University Press.

13

Eastwood, B.J. and Gallant, A.R. (1990) ``Adaptive Rules for Seminnonparametric Estimators that Achieve Asymptotic Normality'', manuscript, North Carolina State University.

14

Andrews, D.W.K. (1991) ``Asymptotic Normality of Series Estimators for Nonparametric and Semiparametric Regression Models'' Econometrica 59 307-345.

15

Gallant, A.R. (1981) ``On the Bias in Flexible Functional Forms and an Essentially Unbiased Form: The Fourier Flexible Form'' Journal of Econometrics 15 211-245.

16

Gallant, A. R. and D.W. Nychka (1989) ``Seminonparametric Maximum Likelihood Estimation'' Econometrica 55, 363-390.

17

Gallant, A.R. and H. White (1992) ``On Learning the Derivatives of an Unknown Mapping with Multilayer Feedforward Networks'' Neural Networks 5 129-138.

18

Gallant, A.R. and H. White (1988) ``The Exists a Neural Network that Does Not Make Avoidable Mistakes'' Proceedings of the Second Annual IEEE Conference on Neural Networks New York IEEE Press, 657-664.

19

White, H. (1990) ``Connectionist Nonparametric Regression: Multilayer Feedforward Networks Can Learn Arbitrary Mappings'' Neural Networks 3 535-549.

20

Hornik, K. Stinchcombe, M. and H. White (1989) ``Multilayer Feedforward Networks are Universal Approximators'' Neural Networks 3 551-560.

21

Yukich, J.E. M.B. Stinchcombe and H. White (1994) ``Sup Norm Approximation Bounds for Networks through Probabilistic Methods'' manuscript, University of California, San Diego.

Simulation Estimation