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As weak lensing surveys become deeper, they reveal more non-Gaussian aspects of the convergence field which can only be extracted using statistics beyond the power spectrum. In Cheng et al. (2020) we showed that the scattering transform, a…

Cosmology and Nongalactic Astrophysics · Physics 2024-10-07 Sihao Cheng , Brice Ménard

Likelihood-free inference provides a rigorous approach to preform Bayesian analysis using forward simulations only. The main advantage of likelihood-free methods is its ability to account for complex physical processes and observational…

Cosmology and Nongalactic Astrophysics · Physics 2022-02-09 Sut-Ieng Tam , Keiichi Umetsu , Adam Amara

In high-dimensional Bayesian statistics, various methods have been developed, including prior distributions that induce parameter sparsity to handle many parameters. Yet, these approaches often overlook the rich spectral structure of the…

Statistics Theory · Mathematics 2025-05-06 Tomoya Wakayama , Masaaki Imaizumi

In this paper we consider a variety of procedures for numerical statistical inference in the family of univariate and multivariate stable distributions. In connection with univariate distributions (i) we provide approximations by finite…

Computation · Statistics 2012-09-04 Efthymios G. Tsionas

In order to extract full cosmological information from next-generation large and high-precision weak lensing (WL) surveys (e.g. Euclid, Roman, LSST), higher-order statistics that probe the small-scale, non-linear regime of large scale…

Cosmology and Nongalactic Astrophysics · Physics 2022-03-01 Alina Sabyr , Zoltán Haiman , José Manuel Zorrilla Matilla , Tianhuan Lu

$ $Weak gravitational lensing is a powerful probe which is used to constrain the standard cosmological model and its extensions. With the enhanced statistical precision of current and upcoming surveys, high accuracy predictions for weak…

Cosmology and Nongalactic Astrophysics · Physics 2023-04-26 Ting Tan , Dominik Zuercher , Janis Fluri , Alexandre Refregier , Federica Tarsitano , Tomasz Kacprzak

We introduce a novel generative formulation of deep probabilistic models implementing "soft" constraints on their function dynamics. In particular, we develop a flexible methodological framework where the modeled functions and derivatives…

Machine Learning · Statistics 2018-06-19 Marco Lorenzi , Maurizio Filippone

Modelling of the weak lensing of the CMB will be crucial to obtain correct cosmological parameter constraints from forthcoming precision CMB anisotropy observations. The lensing affects the power spectrum as well as inducing…

Astrophysics · Physics 2010-11-17 Antony Lewis

Massive cosmic neutrinos change the structure formation history by suppressing perturbations on small scales. Weak lensing data from galaxy surveys probe the structure evolution and thereby can be used to constrain the total mass of the…

Cosmology and Nongalactic Astrophysics · Physics 2019-03-28 Zack Li , Jia Liu , José Manuel Zorrilla Matilla , William R. Coulton

We present methods to rigorously extract parameter combinations that are constrained by data from posterior distributions. The standard approach uses linear methods that apply to Gaussian distributions. We show the limitations of the linear…

Cosmology and Nongalactic Astrophysics · Physics 2022-04-06 Tara Dacunha , Marco Raveri , Minsu Park , Cyrille Doux , Bhuvnesh Jain

The statistics of peaks in weak lensing convergence maps is a promising tool to investigate both the properties of dark matter haloes and constrain the cosmological parameters. We study how the number of detectable peaks and its scaling…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-22 V. F. Cardone , S. Camera , M. Sereno , G. Covone , R. Maoli , R. Scaramella

We investigate whether a Gaussian likelihood, as routinely assumed in the analysis of cosmological data, is supported by simulated survey data. We define test statistics, based on a novel method that first destroys Gaussian correlations in…

Cosmology and Nongalactic Astrophysics · Physics 2017-11-15 Elena Sellentin , Alan F. Heavens

We consider generalized linear regression analysis with left-censored covariate due to the lower limit of detection. Complete case analysis by eliminating observations with values below limit of detection yields valid estimates for…

Methodology · Statistics 2014-12-09 Shengchun Kong , Bin Nan

Weak gravitational lensing provides a unique method to map directly the dark matter in the Universe. The majority of lensing analyses uses the two-point statistics of the cosmic shear field to constrain the cosmological model yielding…

Cosmology and Nongalactic Astrophysics · Physics 2014-11-18 S. Pires , J. -L. Starck , A. Amara , A. Refregier , R. Teyssier

Stochastic systems in biology often exhibit substantial variability within and between cells. This variability, as well as having dramatic functional consequences, provides information about the underlying details of the system's behaviour.…

Quantitative Methods · Quantitative Biology 2015-11-09 Iain G. Johnston

In recent years dynamical modelling has been provided with a range of breakthrough methods to perform exact Bayesian inference. However it is often computationally unfeasible to apply exact statistical methodologies in the context of large…

Computation · Statistics 2014-12-24 Umberto Picchini , Julie Lyng Forman

The weak lensing power spectrum is a powerful tool to probe cosmological parameters. Additionally, lensing peak counts contain cosmological information beyond the power spectrum. Both of these statistics can be affected by the preferential…

Cosmology and Nongalactic Astrophysics · Physics 2014-03-07 Jia Liu , Zoltán Haiman , Lam Hui , Jan M. Kratochvil , Morgan May

Weak lensing convergence can be used directly to map and probe the dark mass distribution in the universe. Building on earlier studies, we recall how the statistics of the convergence field are related to the statistics of the underlying…

Astrophysics · Physics 2009-11-07 Andrew J. Barber , Dipak Munshi , Patrick Valageas

One of the main unsolved problems of cosmology is how to maximize the extraction of information from nonlinear data. If the data are nonlinear the usual approach is to employ a sequence of statistics (N-point statistics, counting statistics…

Cosmology and Nongalactic Astrophysics · Physics 2018-03-07 Uros Seljak , Grigor Aslanyan , Yu Feng , Chirag Modi

The analysis of panel count data has garnered considerable attention in the literature, leading to the development of multiple statistical techniques. In inferential analysis, most works focus on leveraging estimating equation-based…

Methodology · Statistics 2025-10-08 Udita Goswami , Shuvashree Mondal