IDEAS home Printed from https://ideas.repec.org/h/eme/aecozz/s0731-9053(2009)0000024015.html
   My bibliography  Save this book chapter

Analyzing MSI rules for the USA – Extracted from a feedforward neural network

In: Measurement Error: Consequences, Applications and Solutions

Author

Listed:
  • Vincent A. Schmidt
  • Jane M. Binner

Abstract

This chapter introduces a mechanism for generating a series of rules that characterize the money-price relationship for the United States, defined as the relationship between the rate of growth of the money supply and inflation. Monetary Services Indicator (MSI) component data is used to train a selection of candidate feedforward neural networks. The selected network is mined for rules, expressed in human-readable and machine-executable form. The rule and network accuracy are compared, and expert commentary is made on the readability and reliability of the extracted rule set. The ultimate goal of this research is to produce rules that meaningfully and accurately describe inflation in terms of the MSI component dataset.11Paper cleared for public release AFRL/WS–07–0848.

Suggested Citation

  • Vincent A. Schmidt & Jane M. Binner, 2009. "Analyzing MSI rules for the USA – Extracted from a feedforward neural network," Advances in Econometrics, in: Measurement Error: Consequences, Applications and Solutions, pages 281-294, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-9053(2009)0000024015
    DOI: 10.1108/S0731-9053(2009)0000024015
    as

    Download full text from publisher

    File URL: https://www.emerald.com/insight/content/doi/10.1108/S0731-9053(2009)0000024015/full/html?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://www.emerald.com/insight/content/doi/10.1108/S0731-9053(2009)0000024015/full/pdf?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://www.emerald.com/insight/content/doi/10.1108/S0731-9053(2009)0000024015/full/epub?utm_source=repec&utm_medium=feed&utm_campaign=repec&title=10.1108/S0731-9053(2009)0000024015
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1108/S0731-9053(2009)0000024015?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eme:aecozz:s0731-9053(2009)0000024015. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Emerald Support (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.