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Analyzing point patterns with linear structures has recently been of interest in e.g. neuroscience and geography. To detect anisotropy in such cases, we introduce a functional summary statistic, called the cylindrical $K$-function, since it…

统计理论 · 数学 2016-08-29 Jesper Møller , Farzaneh Safavimanesh , Jakob G. Rasmussen

A spatial point pattern is called anisotropic if its spatial structure depends on direction. Several methods for anisotropy analysis have been introduced in the literature. In this paper, we give an overview of nonparametric methods for…

统计方法学 · 统计学 2018-03-01 Tuomas Rajala , Claudia Redenbach , Aila Särkkä , Martina Sormani

We study point processes on $\mathbb S^d$, the $d$-dimensional unit sphere $\mathbb S^d$, considering both the isotropic and the anisotropic case, and focusing mostly on the spherical case $d=2$. The first part studies reduced Palm…

统计方法学 · 统计学 2016-06-14 Jesper Møller , Ege Rubak

In this paper, we propose crossing statistics and its generalization, as a new framework to characterize the anisotropy in a 2D field, e.g. height on a surface, extendable to higher dimensions. By measuring $\nu^+$, the number of…

计算物理 · 物理学 2018-10-12 M. Ghasemi Nezhadhaghighi , S. M. S. Movahed , T. Yasseri , S. M. Vaez Allaei

The fundamental functional summary statistics used for studying spatial point patterns are developed for marked homogeneous and inhomogeneous point processes on the surface of a sphere. These are extended to point processes on the surface…

统计方法学 · 统计学 2024-10-03 Scott Ward , Edward A. K. Cohen , Niall M. Adams

The $K$-function is arguably the most important functional summary statistic for spatial point processes. It is used extensively for goodness-of-fit testing and in connection with minimum contrast estimation for parametric spatial point…

统计理论 · 数学 2023-09-25 Anne Marie Svane , Christophe Biscio , Rasmus Waagepetersen

The K function and its related statistics have been an enduring tool in the analysis of spatial point processes, providing an easy to compute and interpret summary statistic for characterising the interactions between points of one type, or…

统计方法学 · 统计学 2026-05-20 Jake P. Grainger , Tuomas A. Rajala , David J. Murrell , Sofia C. Olhede

The two-point angular correlation function is a traditional method used to search for deviations from expectations of isotropy. In this paper we develop and explore a statistically descriptive three-point method with the intended…

天体物理仪器与方法 · 物理学 2009-10-02 J. D. Hague , B. R. Becker , M. S. Gold , J. A. J. Matthews

There is currently a gap in theory for point patterns that lie on the surface of objects, with researchers focusing on patterns that lie in a Euclidean space, typically planar and spatial data. Methodology for planar and spatial data thus…

统计理论 · 数学 2020-02-11 Scott Ward , Edward A. K. Cohen , Niall Adams

We introduce directional regularity, a new definition of anisotropy for multivariate functional data. Instead of taking the conventional view, which determines anisotropy as a notion of smoothness along a dimension, directional regularity…

统计方法学 · 统计学 2026-05-05 Omar Kassi , Sunny G. W. Wang

This paper is motivated by medical studies in which the same patients with multiple sclerosis are examined at several successive visits and described by fractional anisotropy tract profiles, which can be represented as functions. Since the…

统计方法学 · 统计学 2023-06-07 Katarzyna Kuryło , Łukasz Smaga

In spatial statistics, point processes are often assumed to be isotropic meaning that their distribution is invariant under rotations. Statistical tests for the null hypothesis of isotropy found in the literature are based either on…

统计方法学 · 统计学 2024-04-17 Chiara Fend , Claudia Redenbach

We develop new tools for formal inference and informal model validation in the analysis of spatial point pattern data. The score test is generalized to a "pseudo-score" test derived from Besag's pseudo-likelihood, and to a class of…

统计方法学 · 统计学 2012-05-18 Adrian Baddeley , Ege Rubak , Jesper Møller

The two-point summary statistics is one of the most commonly used tools in the study of cosmological structure. Starting from the theoretical power spectrum defined in the 3D volume and obtained via the process of ensemble averaging, we…

宇宙学与河外天体物理 · 物理学 2023-06-02 Alvise Raccanelli , Zvonimir Vlah

In recent years many procedures have been proposed to check the anisotropy of a dataset. We present a new simple procedure, based on a scale dependent approach, to detect anisotropy signatures in a given distribution with particular…

天体物理仪器与方法 · 物理学 2017-08-23 M. Scuderi , M. De Domenico , A. Insolia , H. Lyberis

Thanks to the recent availability of large surveys, there has been renewed interest in third-order correlation statistics. Measures of third-order clustering are sensitive to the structure of filaments and voids in the universe and are…

天体物理学 · 物理学 2010-11-11 J. M. Loh

This paper introduces a $K$-function for assessing second-order properties of inhomogeneous random measures generated by marked point processes. The marks can be geometric objects like fibers or sets of positive volume, and the presented…

统计方法学 · 统计学 2021-11-11 Anne Marie Svane , Hans Jacob Teglbjærg Stephensen , Rasmus Waagepetersen

A new method for analyzing the morphological features of point patterns is presented. The method is taken from the study of molecular liquids, where it has been introduced for making a statistical description of anisotropic distributions.…

天体物理学 · 物理学 2007-05-23 R. Valdarnini

We investigate the three-point functions of the weak lensing cosmic shear, using both analytic methods and numerical results from N-body simulations. The analytic model, an isolated dark matter halo with a powerlaw profile chosen to fit the…

天体物理学 · 物理学 2009-11-11 K. Benabed , R. Scoccimarro

Prompted by modern technologies in data acquisition, the statistical analysis of spatially distributed function-valued quantities has attracted a lot of attention in recent years. In particular, combinations of functional variables and…

统计方法学 · 统计学 2023-07-12 Matthias Eckardt , Carles Comas , Jorge Mateu
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