Titlebook: Topics in Nonparametric Statistics; Proceedings of the F Michael G. Akritas,S. N. Lahiri,Dimitris N. Politi Conference proceedings 2014 Spr

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Bootstrapping Realized Bipower Variation,atility model in discrete time, we propose a nonparametric i.i.d. bootstrap procedure by resampling the noise innovations based on discrete time returns, and a nonparametric wild bootstrap procedure by generating pseudo-noise that imitates correctly the first and second order properties of the under

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Multiple Testing Approaches for Removing Background Noise from Images,d noise across the frame. The background noise can result from various uncontrollable sources. In such a situation, it has been observed that the performance of a denoising algorithm can be improved considerably if an additional thresholding procedure is performed on the processed image to set low i

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Peak-Load Forecasting Using a Functional Semi-Parametric Approach,ional nature of the data, we introduce a forecasting methodology based on functional regression approach. To avoid the limitations due to the linear specification when one uses the linear model and to the well-known dimensionality effects when one uses the full nonparametric model, we adopt a flexib

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An Open Problem on Strongly Consistent Learning of the Best Prediction for Gaussian Processes,iven the past such that the difference between the predictor and the conditional expectation tends to zero almost surely for all stationary, ergodic, Gaussian processes. We show some related negative and positive findings.

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