we propose a wavelet based regression function estimator for the estimation of the regression function for a sequence of ?-missing random variables with a common one-dimensional probability density function. some asymptotic properties of the proposed estimator based on block thresholding are investigated. it is found that the estimators achieve optimal minimax convergence rates over large class...

Data completeness is one of the most common challenges that hinder performance data analytics platforms. Different studies have assessed effect missing values on different classification models based a single evaluation metric, namely, accuracy. However, accuracy its own misleading measure classifier because it does not consider unbalanced datasets. This paper presents an experimental study ass...

We evaluate explicit atom, united atom, and coarse-grained force fields for molecular dynamics simulation of poly(methyl methacrylate) (PMMA) by comparison to structural and dynamic neutron scattering data. The coarse-grained force field is assigned based on output of the united atom simulation, for which we use an existing force field. The atomic structure of PMMA requires the use of two types...

Cross-linguistically, missing object constructions are sometimes analyzed as involving long-distance dependencies, similar to the dependencies found in whquestion or relative clause constructions. Other missing object constructions have been analyzed as involving complex predicate formation. We propose that both classes of missing object constructions are found in English, exemplified by the ca...

An extension for univariate kernels that deals with missing values is proposed. These extended kernels are shown to be valid Mercer kernels and can adapt to many types of variables, such as categorical or continuous. The proposed kernels are tested against standard RBF kernels in a variety of benchmark problems showing different amounts of missing values and variable types. Our experimental res...