Related papers: Detection of a small shift in a broad distribution
OPERA(Oscillation Project with Emulsion-tRacking Apparatus) is a new detector concept, iron(lead)-emulsion for a long-baseline neutrino oscillation experiment. This experiment would perform an appearance search for nu_mu-nu_tau oscillation…
Equality-constrained models naturally arise in problems in which measurements are taken at different levels of resolution. The challenge in this setting is that the models usually induce a joint distribution which is intractable. Resorting…
Thermal or finite-size scaling analyses of importance sampling Monte Carlo time series in the vicinity of phase transition points often combine different estimates for the same quantity, such as a critical exponent, with the intent to…
We propose a new Monte Carlo algorithm for complex discrete distributions. The algorithm is motivated by the N-Fold Way, which is an ingenious event-driven MCMC sampler that avoids rejection moves at any specific state. The N-Fold Way can…
Over the last decade, many experiments have demonstrated that nanobiosensors based on Nanotubes and Nanowires are significantly more sensitive compared to their planar counterparts. Yet, there has been persistent gap between reports of…
Recently, there has been a significant amount of interest in satellite telemetry anomaly detection (AD) using neural networks (NN). For AD purposes, the current approaches focus on either forecasting or reconstruction of the time series,…
The NPDGamma experiment measures the asymmetry in $\gamma$-ray emission in the capture of polarized neutrons on liquid parahydrogen. The beam polarization is measured using $^3$He spin analysis, but this measurement does not account for the…
Consider a large number of detectors each generating a data stream. The task is to detect online, distribution changes in a small fraction of the data streams. Previous approaches to this problem include the use of mixture likelihood ratios…
The standard Kernel Quadrature method for numerical integration with random point sets (also called Bayesian Monte Carlo) is known to converge in root mean square error at a rate determined by the ratio $s/d$, where $s$ and $d$ encode the…
In general, the statistical simulation approaches are referred to as the Monte Carlo methods as a whole. The broad class of the Monte Carlo methods involves the Markov chain Monte Carlo (MCMC) techniques that attract the attention of…
Large-scale datasets are increasingly being used to inform decision making. While this effort aims to ground policy in real-world evidence, challenges have arisen as selection bias and other forms of distribution shifts often plague…
In the OPERA experiment, the time of arrival of the neutrino light curve at LNGS is defined by a best-fit to the generating proton PDF at CERN. By a two parameter matched filtering procedure, we determine that the OPERA neutrino light curve…
At the KATRIN experiment, the electron antineutrino mass is inferred from the shape of the $\beta$-decay spectrum of tritium. Important systematic effects in the Windowless Gaseous Tritium Source (WGTS) of the experiment include the energy…
The OPERA experiment reached its main goal by proving the appearance of $\nu_{\tau}$ in the CNGS $\nu_{\mu} $ beam. A sample of five $\nu_{\tau}$ candidates was collected allowing to reject the null hypothesis at $5.1 \sigma$. The…
Most studies in real time change-point detection either focus on the linear model or use the CUSUM method under classical assumptions on model errors. This paper considers the sequential change-point detection in a nonlinear quantile model.…
Monte Carlo (MC) dropout is one of the state-of-the-art approaches for uncertainty estimation in neural networks (NNs). It has been interpreted as approximately performing Bayesian inference. Based on previous work on the approximation of…
Subsampling is a general statistical method developed in the 1990s aimed at estimating the sampling distribution of a statistic $\hat \theta _n$ in order to conduct nonparametric inference such as the construction of confidence intervals…
Individual-based models of contagious processes are useful for predicting epidemic trajectories and informing intervention strategies. In such models, the incorporation of contact network information can capture the non-randomness and…
Using Monte Carlo simulations of perturbations induced by cosmic strings on the microwave background, we demonstrate the scale invariance of string fluctuation patterns. By comparing string-induced fluctuation patterns with gaussian random…
As deeper observations discover increasingly distant galaxies, characterizing the properties of high-redshift galaxy populations will become increasingly challenging and paramount. We present a method for measuring the clustering bias of…