Recursive bias estimation and L2 boosting

Journal Article · Thu Jan 01 04:00:00 EST 2009

OSTI ID:956561

Hengartner, Nicolas W ^[1]; Cornillon, Pierre - Andre ^[2]; Matzner - Lober, Eric ^[3]

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1. Los Alamos National Laboratory
2. INRA, FRANCE
3. RENNE, FRANCE

This paper presents a general iterative bias correction procedure for regression smoothers. This bias reduction schema is shown to correspond operationally to the L{sub 2} Boosting algorithm and provides a new statistical interpretation for L{sub 2} Boosting. We analyze the behavior of the Boosting algorithm applied to common smoothers S which we show depend on the spectrum of I - S. We present examples of common smoother for which Boosting generates a divergent sequence. The statistical interpretation suggest combining algorithm with an appropriate stopping rule for the iterative procedure. Finally we illustrate the practical finite sample performances of the iterative smoother via a simulation study.

• Research Organization: Los Alamos National Laboratory (LANL)
• Sponsoring Organization: DOE
• DOE Contract Number: AC52-06NA25396
• OSTI ID: 956561
• Report Number(s): LA-UR-09-01177; LA-UR-09-1177
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
ABSORPTION
ALGORITHMS
CORRECTIONS
DATA ANALYSIS
KERNELS
REDUCTION
REGRESSION ANALYSIS
SIMULATION
SPLINE FUNCTIONS