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In 2020, two novel distributions for the analysis of directional data were introduced: the spherical Cauchy distribution and the Poisson kernel-based distribution. This paper provides a detailed exploration of both distributions within…

Methodology · Statistics 2025-02-20 Michail Tsagris , Panagiotis Papastamoulis , Shogo Kato

In recent decades novel solid substrates have been designed which change their wettability in response to light or an electrostatic field. Here, we investigate a droplet on substrates with oscillating uniform wettability by varying minimium…

Fluid Dynamics · Physics 2021-10-28 Josua Grawitter , Holger Stark

The modelling of data on a spherical surface requires the consideration of directional probability distributions. To model asymmetrically distributed data on a three-dimensional sphere, Kent distributions are often used. The moment…

Machine Learning · Computer Science 2015-06-29 Parthan Kasarapu

We investigate the estimation of a weighted density taking the form $g=w(F)f$, where $f$ denotes an unknown density, $F$ the associated distribution function and $w$ is a known (non-negative) weight. Such a class encompasses many examples,…

Statistics Theory · Mathematics 2017-03-13 Fabien Navarro , Christophe Chesneau , Jalal Fadili

Nonparametric density estimators are studied for $d$-dimensional, strongly spatial mixing data which is defined on a general $N$-dimensional lattice structure. We consider linear and nonlinear hard thresholded wavelet estimators which are…

Statistics Theory · Mathematics 2017-12-27 Johannes T. N. Krebs

Z pinches produce an X ray rich plasma environment where backlighting imaging of imploding targets can be quite challenging to analyze. What is required is a detailed understanding of the implosion dynamics by studying snapshot images of…

Plasma Physics · Physics 2012-11-13 Bedros Afeyan , Kirk Won , Jean Luc Starck , Michael Cuneo

A theory of superefficiency and adaptation is developed under flexible performance measures which give a multiresolution view of risk and bridge the gap between pointwise and global estimation. This theory provides a useful benchmark for…

Statistics Theory · Mathematics 2007-06-13 T. Tony Cai , Mark G. Low

Wettability is the affinity of a liquid for a solid surface. For energetic reasons, macroscopic drops of liquid are nearly spherical away from interfaces with solids, and any local deformations due to molecular-scale surface interactions…

Mesoscale and Nanoscale Physics · Physics 2017-11-27 Ronaldo Giro , Peter W. Bryant , Michael Engel , Rodrigo F. Neumann , Mathias Steiner

A nontrivial topology of the spatial section of the universe is an observable, which can be probed for all locally homogeneous and isotropic universes, without any assumption on the cosmological density parameters. We discuss how one can…

Astrophysics · Physics 2008-11-26 M. J. Reboucas

In this paper we make progress on the unsupervised task of mining arbitrarily shaped clusters in highly noisy datasets, which is a task present in many real-world applications. Based on the fundamental work that first applies a wavelet…

Databases · Computer Science 2019-01-08 Zengjian Chen , Jiayi Liu , Yihe Deng , Kun He , John E. Hopcroft

Weak gravitational lensing, resulting from the bending of light due to the presence of matter along the line of sight, is a potent tool for exploring large-scale structures, particularly in quantifying non-Gaussianities. It stands as a…

Cosmology and Nongalactic Astrophysics · Physics 2024-06-17 Vilasini Tinnaneri Sreekanth , Sandrine Codis , Alexandre Barthelemy , Jean-Luc Starck

A new data-based smoothing parameter for circular kernel density (and its derivatives) estimation is proposed. Following the plug-in ideas, unknown quantities on an optimal smoothing parameter are replaced by suitable estimates. This paper…

Computation · Statistics 2022-11-21 Jose Ameijeiras-Alonso

We use an all--sky, complete sample of nearby galaxies, extracted from the LEDA data base, to map the optical galaxy density field in the nearby universe. In order to determine this field, we correct the redshift--dependent distances by…

Astrophysics · Physics 2007-05-23 C. Marinoni , G. Giuricin , B. Costantini , P. Monaco

We present a new approach to measure the shapes of galaxies, a fundamental task in observational astronomy. This approach is based on the decomposition of a galaxy image into a series of orthogonal basis functions, or `shapelets'. Our…

Astrophysics · Physics 2017-08-23 Alexandre Refregier , Tzu-Ching Chang , David Bacon

We present a method to simulate deep sky images, including realistic galaxy morphologies and telescope characteristics. To achieve a wide diversity of simulated galaxy morphologies, we first use the shapelets formalism to parametrize the…

This paper is concerned with adaptive kernel estimation of the L\'evy density N(x) for bounded-variation pure-jump L\'evy processes. The sample path is observed at n discrete instants in the "high frequency" context (\Delta = \Delta(n)…

Statistics Theory · Mathematics 2013-02-14 Mélina Bec , Claire Lacour

Switchable and adaptive substrates emerged as valuable tools for the control of wetting and actuation of droplet motion. Here we report a computational study of the dynamics of an unstable thin liquid film deposited on a switchable…

Fluid Dynamics · Physics 2024-01-03 Stefan Zitz , Andrea Scagliarini , Jens Harting

The transport of an infinitely thin, hard rod in a random, dense array of point obstacles is investigated by molecular dynamics simulations. Our model mimics the sterically hindered dynamics in dense needle liquids. The center-of-mass…

Statistical Mechanics · Physics 2008-09-22 Felix Höfling , Erwin Frey , Thomas Franosch

In many practical settings one can sequentially and adaptively guide the collection of future data, based on information extracted from data collected previously. These sequential data collection procedures are known by different names,…

Statistics Theory · Mathematics 2013-11-28 Ervin Tánczos , Rui M. Castro

Large-scale structure (LSS) analysis in galaxy surveys is a powerful cosmological probe but is limited by tracer bias, which can obscure underlying information and weaken parameter constraints. Existing methods either model bias or restrict…

Cosmology and Nongalactic Astrophysics · Physics 2025-12-01 Zhujun Jiang , Xiaolin Luo , Wenying Du , Zhiwei Min , Fenfen Yin , Longlong Feng , Jiacheng Ding , Le Zhang , Xiao-Dong Li