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Connectionist Non-parametric Regression Multilayer Feedforward Networks Can Learn Arbitrary Mappings

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Author Info
Halbert White

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Abstract

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Publisher Info
Paper provided by Department of Economics, UC San Diego in its series University of California at San Diego, Economics Working Paper Series with number 90-5.

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Date of creation: Jan 1990
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Handle: RePEc:cdl:ucsdec:90-5

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  1. F. Gonzalez Miranda, N. Burgess, 1997. "Modelling market volatilities: the neural network perspective," European Journal of Finance, Taylor and Francis Journals, vol. 3(2), pages 137-157, June. [Downloadable!] (restricted)
  2. Norman R. Swanson & Halbert White, 1995. "A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Macroeconomics 9503004, EconWPA. [Downloadable!]
    Other versions:
  3. Gábor Lugosi & Andrew B. Nobel, 1998. "Adaptive Model Selection Using Empirical Complexities," Economics Working Papers 323, Department of Economics and Business, Universitat Pompeu Fabra. [Downloadable!]
  4. Xiaohong Chen & Halbert White, 1997. "Improved Rates and Asymptotic Normality for Nonparametric Neural Network Estimators," University of California at San Diego, Economics Working Paper Series 97-11, Department of Economics, UC San Diego. [Downloadable!]
  5. Joseph Brian Adams, 1999. "Predicting pickle harvests using a parametric feedforward neural network," Journal of Applied Statistics, Taylor and Francis Journals, vol. 26(2), pages 165-176, February. [Downloadable!] (restricted)
  6. Jürgen Franke & Jean-Pierre Stockis & Joseph Tadjuidje, 2007. "Quantile Sieve Estimates For Time Series," SFB 649 Discussion Papers SFB649DP2007-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
  7. R. Glen Donaldson & Mark Kamstra, . "Forecasting Fundamental Asset Return Distributions," Computing in Economics and Finance 1997 176, Society for Computational Economics. [Downloadable!]
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