Nonparametric density estimation from observations with multiplicative measurement errors

Estimation in Nonparametric Regression with Nonregular Errors

For sufficiently nonregular distributions with bounded support, the extreme observations converge to the boundary points at a faster rate than the square root of the sample size. In a nonparametric regression model with such a nonregular error distribution, this fact can be used to construct an estimator for the regression function that converges at a faster rate than the Nadaraya– Watson estim...

Sequential nonparametric density estimation

Nonparametric volatility density estimation

B E RT VA N E S , P E T E R S P R E I J 1 and HARRY VAN ZANTEN 2 Korteweg-de Vries Institute for Mathematics, University of Amsterdam, Plantage Muidergracht 24, 1018 TV Amsterdam, The Netherlands. E-mail: [email protected]; [email protected] Division of Mathematics and Computer Science, Faculty of Sciences, Free University Amsterdam, De Boelelaan 1081a, 1081 HV Amsterdam, The Netherlands...

Nonparametric Estimation in a Multiplicative Censoring Model with Symmetric Noise

Abstract. We consider the model Yi “ XiUi, i “ 1, . . . , n, where the Xi, the Ui and thus the Yi are all independent and identically distributed. The Xi have density f and are the variables of interest, the Ui are multiplicative noise with uniform density on r1 ́ a, 1` as, for some 0 ă a ă 1, and the two sequences are independent. However, only the Yi are observed. We study nonparametric estima...

Statistical Topology Using the Nonparametric Density Estimation and Bootstrap Algorithm

This paper presents approximate confidence intervals for each function of parameters in a Banach space based on a bootstrap algorithm. We apply kernel density approach to estimate the persistence landscape. In addition, we evaluate the quality distribution function estimator of random variables using integrated mean square error (IMSE). The results of simulation studies show a significant impro...