TY - JOUR
T1 - High order data sharpening for density estimation
AU - Hall, Peter
AU - Minnotte, Michael C.
PY - 2002
Y1 - 2002
N2 - It is shown that data sharpening can be used to produce density estimators that enjoy arbitrarily high orders of bias reduction. Practical advantages of this approach, relative to competing methods, are demonstrated. They include the sheer simplicity of the estimators, which makes code for computing them particularly easy to write, very good mean-squared error performance, reduced 'wiggliness' of estimates and greater robustness against undersmoothing.
AB - It is shown that data sharpening can be used to produce density estimators that enjoy arbitrarily high orders of bias reduction. Practical advantages of this approach, relative to competing methods, are demonstrated. They include the sheer simplicity of the estimators, which makes code for computing them particularly easy to write, very good mean-squared error performance, reduced 'wiggliness' of estimates and greater robustness against undersmoothing.
KW - Bandwidth
KW - Bias reduction
KW - Kernel methods
KW - Local polynomial methods
KW - Mean-squared error
KW - Nonparametric curve estimation
KW - Transformation methods
KW - Wiggliness
UR - http://www.scopus.com/inward/record.url?scp=0036003422&partnerID=8YFLogxK
U2 - 10.1111/1467-9868.00329
DO - 10.1111/1467-9868.00329
M3 - Article
SN - 1369-7412
VL - 64
SP - 141
EP - 157
JO - Journal of the Royal Statistical Society. Series B: Statistical Methodology
JF - Journal of the Royal Statistical Society. Series B: Statistical Methodology
IS - 1
ER -