A Dimension Reduction Approach to the Study of City Family-income Distributions Via Sliced Inverse Regression
Sliced inverse regression is a dimension reduction technique for exploring non-linear relationships between an output variable and a vector of input variables. Motivated by a data set of income distributions and economic indicators of french cities, we adress the problem of modelling a family of empirical distribution functions in terms of some covariates. SIR allows us to visually explore the ralationship between the covariates and several important features of the income distributions. A stochastic ordering is revealed for the French city income distributions.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||1996|
|Date of revision:|
|Contact details of provider:|| Postal: GREMAQ, Universite de Toulouse I Place Anatole France 31042 - Toulouse CEDEX France.|
Fax: 05 61 22 55 63
Web page: http://www-gremaq.univ-tlse1.fr/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:fth:gremaq:96.438. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel)
If references are entirely missing, you can add them using this form.