Genome-wide expression quantitative trait loci (eQTL) studies have emerged as a powerful tool to understand the genetic basis of gene expression and complex traits. In a typical eQTL study, the huge number of genetic markers and expression traits and their complicated correlations present a challenging multiple-testing correction problem. The resampling-based test using permutation or bootstrap...

The integral equation arising from space variant 2-D texture res-ampling is reformulated through wavelet analysis. We transform the standard convolution integral in texture space into an inner product over sparse representations for both the texture and the warped lter function. This yields an algorithm that operates in constant time in the area of the domain of convolution, and that is sensiti...

Particle filters estimate the state of dynamic systems through Bayesian interference and stochastic sampling techniques. Parallel/distributed particle filters aim to improve the performance by deploying all particles on different processing units. However, the communication cost of transferring particles is high due to the centralized processing in resampling step. To reduce the communication c...

This paper introduces a simple method of two-stage resampling where Fourier-domain up-sampling is followed by traditional resampling. Practical aspects as well as efficient implementation techniques are considered. A new version of pruned FFT algorithms to calculate the up-sampling stage is also introduced. The suggested two-stage resampling method provides very high-quality results exceeding t...

In many real-world binary classification tasks (e.g. detection of certain objects from images), an available dataset is imbalanced, i.e., it has much less representatives of a one class (a minor class), than of another. Generally, accurate prediction of the minor class is crucial but it’s hard to achieve since there is not much information about the minor class. One approach to deal with this p...

For any probability space and a collection of events we give an algorithmic proof of the Lovász Local Lemma if there is a resampling oracle for each event. The resampling oracles act as an abstraction layer that isolates the details of the proof from the details of the probability space. The number of resamplings performed by the algorithm is bounded by expressions similar to those obtained by ...

Interim sample size re-estimation (SSR) often affects the Type I and II error rates. We propose and investigate a method based on resampling the whole study design at the interim analysis. This resampling starts with SSR at the observed interim analysis values of nuisance parameters and finishes with the decision to accept or reject the null hypothesis. The proposed approach finds a new critica...

Resampling is a common operation in digital image processing systems. The standard procedure involves the (conceptual) reconstruction of a continuous image succeeded by sampling on the new lattice sites. When the reconstruction is done by classical interpolation functions, results might be sub-optimal because the information loss is not minimized. In the particular case of subsampling (i.e., re...

With resampling, a regularly sampled signal is extracted from observations which are irregularly spaced in time. Resampling methods can be divided into simple and complex methods. Simple methods such as Sample&Hold (S&H) and Nearest Neighbor Resampling (NNR) use only one irregular sample for one resampled observation. A theoretical analysis of the simple methods is given. The various resampling...

This paper evaluates bootstrap inference methods for quantile regression panel data models. We propose to construct confidence intervals for the parameters of interest using percentile bootstrap with pairwise resampling. We study three different bootstrapping procedures. First, the bootstrap samples are constructed by resampling only from cross-sectional units with replacement. Second, the temp...