Variable selection for functional density trees

Shu-Fu Kuo and Yu-Shan Shih

Journal of Applied Statistics, 2012, vol. 39, issue 7, 1387-1395

Abstract: In this paper, the exhaustive search principle used in functional trees for classifying densities is shown to select variables with more split points. A new variable selection scheme is proposed to correct this bias. The Pearson chi-squared tests for associated two-way contingency tables are used to select the variables. Through simulation, we show that the new method can control bias and is more powerful in selecting split variable.

Date: 2012
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DOI: 10.1080/02664763.2011.649717

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