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Given a random sample of points from some unknown density, we propose a data-driven method for estimating density level sets under the r-convexity assumption. This shape condition generalizes the convexity property. However, the main…

Statistics Theory · Mathematics 2019-05-09 Alberto Rodríguez-Casal , Paula Saavedra-Nieves

A cluster tree provides a highly-interpretable summary of a density function by representing the hierarchy of its high-density clusters. It is estimated using the empirical tree, which is the cluster tree constructed from a density…

Statistics Theory · Mathematics 2017-02-14 Jisu Kim , Yen-Chi Chen , Sivaraman Balakrishnan , Alessandro Rinaldo , Larry Wasserman

The aim here is to address the origins of sustainability for the real growth rate in the United States. For over a century of observations on the real GDP per capita of the United States a sustainable two percent growth rate has been…

General Finance · Quantitative Finance 2016-08-08 Ali Hosseiny

Neutrosophic Statistics means statistical analysis of population or sample that has indeterminate (imprecise, ambiguous, vague, incomplete, unknown) data. For example, the population or sample size might not be exactly determinate because…

Artificial Intelligence · Computer Science 2014-06-10 Florentin Smarandache

We study a stochastic model of urban growth generating spatial distributions of population densities at an intermediate mesoscopic scale. The model is based on the antagonist interplay between the two opposite abstract processes of…

Physics and Society · Physics 2018-11-21 Juste Raimbault

The evolution of two species with different fitness is investigated on degree-heterogeneous graphs. The population evolves either by one individual dying and being replaced by the offspring of a random neighbor (voter model (VM) dynamics)…

Populations and Evolution · Quantitative Biology 2009-11-13 T. Antal , S. Redner , V. Sood

Multivariate hypergeometric distribution arises frequently in elementary statistics and probability courses, for simultaneously studying the occurence law of specified events, when sampling without replacement from a finite population with…

Statistics Theory · Mathematics 2021-01-05 X. G. Duan

Multiple importance sampling estimators are widely used for computing intractable constants due to its reliability and robustness. The celebrated balance heuristic estimator belongs to this class of methods and has proved very successful in…

Computation · Statistics 2019-09-05 Felipe J Medina-Aguayo , Richard G Everitt

The study of human mobility patterns is a crucially important research field for its impact on several socio-economic aspects and, in particular, the measure of regularity patters of human mobility can provide a across-the-board view of…

Physics and Society · Physics 2021-04-20 Fabio Vanni , David Lambert

The scaling relations between city attributes and population are emergent and ubiquitous aspects of urban growth. Quantifying these relations and understanding their theoretical foundation, however, is difficult due to the challenge of…

Physics and Society · Physics 2023-01-31 Keith Burghardt , Johannes H. Uhl , Kristina Lerman , Stefan Leyk

A good understanding of cities is crucial to implement urban planning policies leading to social and economic sustainability and an efficient use of resources. While urban concentration has been associated with both positive and negative…

Physics and Society · Physics 2025-09-09 Gaëtan Laziou , Rémi Lemoy

We study a generalised model of population growth in which the state variable is population growth rate instead of population size. Stochastic parametric perturbations, modelling phenotypic variability, lead to a Langevin system with two…

Populations and Evolution · Quantitative Biology 2010-10-15 Harold P. de Vladar , Ido Pen

Bayesian inverse problem on an infinite dimensional separable Hilbert space with the whole state observed is well posed when the prior state distribution is a Gaussian probability measure and the data error covariance is a cylindric…

Probability · Mathematics 2017-01-31 Ivan Kasanický , Jan Mandel

We study hierarchical clusterings of metric spaces that change over time. This is a natural geometric primitive for the analysis of dynamic data sets. Specifically, we introduce and study the problem of finding a temporally coherent…

Data Structures and Algorithms · Computer Science 2017-10-23 Tamal K. Dey , Alfred Rossi , Anastasios Sidiropoulos

We address the problem of crowd localization, i.e., the prediction of dots corresponding to people in a crowded scene. Due to various challenges, a localization method is prone to spatial semantic errors, i.e., predicting multiple dots…

Computer Vision and Pattern Recognition · Computer Science 2020-12-24 Shahira Abousamra , Minh Hoai , Dimitris Samaras , Chao Chen

When data are stored across multiple locations, directly pooling all the data together for statistical analysis may be impossible due to communication costs and privacy concerns. Distributed computing systems allow the analysis of such…

Methodology · Statistics 2025-02-27 Xian Li , Xuan Liang , A. H. Welsh , Tao Zou

Galor discovered many mysteries of the growth process. He lists them in his Unified Growth Theory and wonders how they can be explained. Close inspection of his mysteries reveals that they are of his own creation. They do not exist. He…

General Finance · Quantitative Finance 2016-04-21 Ron W Nielsen

The well-being of individuals in a crowd is interpreted as a product of the crossover of individuals from heterogeneous communities, which may occur via interactions with other crowds. The index moving-direction entropy corresponding to the…

General Economics · Economics 2023-12-06 Yukio Ohsawa , Sae Kondo , Yi Sun , Kaira Sekiguchi

H-measures and semiclassical (Wigner) measures were introduced in earlyn 1990s and since then they have found numerous applications in problems involving $\mathrm{L}^2$ weakly converging sequences. Although they are similar objects, neither…

Analysis of PDEs · Mathematics 2023-09-06 Nenad Antonić , Marko Erceg

Density level sets can be estimated using plug-in methods, excess mass algorithms or a hybrid of the two previous methodologies. The plug-in algorithms are based on replacing the unknown density by some nonparametric estimator, usually the…

Statistics Theory · Mathematics 2016-11-26 A. Rodríguez-Casal , P. Saavedra-Nieves
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