caa a22 4500 475826744 CHVBK 20180406123830.0 cr unu---uuuuu 170329e20001201xx s 000 0 eng 10.1023/A:1017564907869 doi (NATIONALLICENCE)springer-10.1023/A:1017564907869 Boundary Bias Correction for Nonparametric Deconvolution [Elektronische Daten] [Shunpu Zhang, Rohana Karunamuni] In this paper we consider the deconvolution problem in nonparametric density estimation. That is, one wishes to estimate the unknown density of a random variable X, say f X , based on the observed variables Y's, where Y = X + ∈ with ∈ being the error. Previous results on this problem have considered the estimation of f X at interior points. Here we study the deconvolution problem for boundary points. A kernel-type estimator is proposed, and its mean squared error properties, including the rates of convergence, are investigated for supersmooth and ordinary smooth error distributions. Results of a simulation study are also presented. The Institute of Statistical Mathematics, 2000 Deconvolution nationallicence density estimation nationallicence boundary effects nationallicence bandwidth variation nationallicence Zhang Shunpu Department of Mathematical Sciences, University of Alberta, T6G 2G1, Edmonton, Alberta, Canada aut Karunamuni Rohana Department of Mathematical Sciences, University of Alberta, T6G 2G1, Edmonton, Alberta, Canada aut Annals of the Institute of Statistical Mathematics Kluwer Academic Publishers 52/4(2000-12-01), 612-629 0020-3157 52:4<612 2000 52 10463 https://doi.org/10.1023/A:1017564907869 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1017564907869 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhang Shunpu Department of Mathematical Sciences, University of Alberta, T6G 2G1, Edmonton, Alberta, Canada aut NATIONALLICENCE 700 1- Karunamuni Rohana Department of Mathematical Sciences, University of Alberta, T6G 2G1, Edmonton, Alberta, Canada aut NATIONALLICENCE 773 0- Annals of the Institute of Statistical Mathematics Kluwer Academic Publishers 52/4(2000-12-01), 612-629 0020-3157 52:4<612 2000 52 10463 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer