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Smoothing ordered sparse contingency tables and the Chi-Squared test

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Author Info
Klaus Abberger () (IFO Munich)

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Abstract

To estimate cell probabilities for ordered sparse contingency tables several smooth- ing techniques have been investigated. It has been recognized that nonparametric smoothing methods provide estimators of cell probabilities that have better performance than the pure frequency estimators. With the help of simulation examples it is shown in this paper that these smoothing techniques may help to get test which are more powerful than Chi-Squared test with raw data. But the distribution of the Chi-Squared statistics after smoothing is unknown. This distribution can also be estimated by simulation methods.

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File URL: http://cofe.uni-konstanz.de/Papers/dp02_09.pdf
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Publisher Info
Paper provided by Center of Finance and Econometrics, University of Konstanz in its series CoFE Discussion Paper with number 02-09.

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Length: 9 pages
Date of creation: Mar 2002
Date of revision:
Handle: RePEc:knz:cofedp:0209

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Related research
Keywords: nonparametric estimation; local polynomial smoothers; local likelihood; sparse contingency tables; Chi-Squared test; independence test;

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This page was last updated on 2009-11-26.


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