Related papers: A generalizable method for estimating meteor showe…
We consider bandwidth matrix selection for kernel density estimators (KDEs) of density level sets in $\mathbb{R}^d$, $d \ge 2$. We also consider estimation of highest density regions, which differs from estimating level sets in that one…
Online change detection involves monitoring a stream of data for changes in the statistical properties of incoming observations. A good change detector will detect any changes shortly after they occur, while raising few false alarms.…
Modal regression estimates the local modes of the distribution of $Y$ given $X=x$, instead of the mean, as in the usual regression sense, and can hence reveal important structure missed by usual regression methods. We study a simple…
Based on telescopic observations of Jupiter-family comets (JFCs), there is predicted to be a paucity of objects at sub-kilometre sizes. However, several bright fireballs and some meteorites have been tenuously linked to the JFC population,…
We present a parameterized model of atmospheric particle showers initiated by cosmic rays. Few physics shower parameters are tuned in a comparison to the Conex generator. Resulting shower properties are studied, with a comment on the cases…
The DEEP-South photometric census of small Solar System bodies produces massive time-series data of variable, transient or moving objects as a by-product. To fully investigate unexplored variable phenomena, we present an application of…
We report on an eight year survey of simultaneous optical and radar meteor detections with the goal of isolating the fraction of meteors missed by specular radars. A total of 10,503 Electron Multiplied Charge Couple Device (EMCCD) meteors…
As the third paper in a series regarding the estimation of luminosity functions (LFs) via kernel density estimation (KDE), we present a further generalization of our framework by extending its applicability to multiple flux-limited samples.…
In the present work we carry out a study of the high energy cosmic rays mass identification capabilities of a hybrid detector employing both fluorescence telescopes and particle detectors at ground using simulated data. It involves the…
When nonlinear measures are estimated from sampled temporal signals with finite-length, a radius parameter must be carefully selected to avoid a poor estimation. These measures are generally derived from the correlation integral which…
This article presents a new tool for the automatic detection of meteors. Fast Meteor Detection Toolbox (FMDT) is able to detect meteor sightings by analyzing videos acquired by cameras onboard weather balloons or within airplane with…
We derive the divergence-kernel formula for the linear response of random dynamical systems. Specifically, the pathwise expression is for the parameter-derivative of the marginal or stationary density, not an averaged observable. Our…
This paper addresses the deconvolution problem of estimating a square-integrable probability density from observations contaminated with additive measurement errors having a known density. The estimator begins with a density estimate of the…
We introduce shower deconstruction, a method to look for new physics in a hadronic environment. The method aims to be a full information approach using small jets. It assigns to each event a number chi that is an estimate of the ratio of…
Studies of the relationships between environmental exposures and adverse health outcomes often rely on a two-stage statistical modeling approach, where exposure is modeled/predicted in the first stage and used as input to a separately fit…
Density estimation is a central task in statistics and machine learning. This problem aims to determine the underlying probability density function that best aligns with an observed data set. Some of its applications include statistical…
The mass composition of high energy cosmic rays above $10^{17}$ eV is a crucial issue to solve some open questions in astrophysics such as the acceleration and propagation mechanisms. Unfortunately, the standard procedures to identify the…
In this paper we revisit the kernel density estimation problem: given a kernel $K(x, y)$ and a dataset of $n$ points in high dimensional Euclidean space, prepare a data structure that can quickly output, given a query $q$, a…
Diffusion models now set the benchmark in high-fidelity generative sampling, yet they can, in principle, be prone to memorization. In this case, their learned score overfits the finite dataset so that the reverse-time SDE samples are mostly…
Fireballs (bolides) are high-energy luminous phenomena produced when meteoroids and small asteroids enter Earth's atmosphere at hypersonic speeds, often resulting in fragmentation or complete disintegration accompanied by significant energy…