Related papers: Non-Gaussianity and direction dependent systematic…

We show how observations of the evolution of the galaxy cluster number abundance can be used to constrain primordial non-Gaussianity in the universe. We carry out a maximum likelihood analysis incorporating a number of current datasets and…

Determinantal point processes (a.k.a. DPPs) have recently become popular tools for modeling the phenomenon of negative dependence, or repulsion, in data. However, our understanding of an analogue of a classical parametric statistical theory…

Measurements of the Hubble-Lema\^{i}tre constant ($H_0$) require us to estimate the distance and recession velocity of galaxies independently. Gravitational clustering that leads to the formation of galaxies and the large scale structure…

Robustness of any statistics depends upon the number of assumptions it makes about the measured data. We point out the advantages of median statistics using toy numerical experiments and demonstrate its robustness, when the number of…

Identifying statistical dependence between the features and the label is a fundamental problem in supervised learning. This paper presents a framework for estimating dependence between numerical features and a categorical label using…

Tail dependence refers to clustering of extreme events. In the context of financial risk management, the clustering of high-severity risks has a devastating effect on the well-being of firms and is thus of pivotal importance in risk…

Standard present day large-scale structure (LSS) analyses make a major assumption in their Bayesian parameter inference --- that the likelihood has a Gaussian form. For summary statistics currently used in LSS, this assumption, even if the…

We study the accuracy of estimating the covariance and the precision matrix of a $D$-variate sub-Gaussian distribution along a prescribed subspace or direction using the finite sample covariance. Our results show that the estimation…

It has recently been proposed that the large-scale bias of dark matter halos depends sensitively on primordial non-Gaussianity of the local form. In this paper we point out that the strong scale dependence of the non-Gaussian halo bias…

We present a novel distribution-free approach, the data-driven threshold machine (DTM), for a fundamental problem at the core of many learning tasks: choose a threshold for a given pre-specified level that bounds the tail probability of the…

Accurate measurement of the Hubble constant from standard sirens such as the gravitational wave (GW) sources with electromagnetic counterparts relies on the robust peculiar velocity correction of the redshift of the host galaxy. We show in…

We use supernovae measurements, calibrated by the local determination of the Hubble constant $H_0$ by SH0ES, to interpolate the distance-redshift relation using Gaussian process regression. We then predict, independent of the cosmological…

In this work, we propose a cosmological model-independent and non-local method to constrain the Hubble Constant $H_0$. Inspired by the quasi cosmological model-independent and $H_0$-free properties of the `shifted' Hubble diagram of HII…

Recent NMR experiments on $YBa_2(Cu_{1-x}Ni_x)_3O_{6+\delta}$ (Bobroff et al. Phys. Rev. Lett. 79, 2117 (1997)) have shown that Ni impurities provide an important probe for the momentum dependence of the static spin susceptibility…

Models for extreme values accommodating non-stationarity have been amply studied and evaluated from a parametric perspective. Whilst these models are flexible, in the sense that many parametrizations can be explored, they assume an…

This paper gives a review of concentration inequalities which are widely employed in non-asymptotical analyses of mathematical statistics in a wide range of settings, from distribution-free to distribution-dependent, from sub-Gaussian to…

We obtain a robust, non-parametric, estimate of the Hubble constant from galaxy linear diameters calibrated using HST Cepheid distances. Our method is independent of the parametric form of the diameter function and the spatial distribution…

This paper develops a general approach to characterize the long-time trajectory behavior of nonconvex gradient descent in generalized single-index models in the large aspect ratio regime. In this regime, we show that for each iteration the…

We combine Dark Energy Survey Year 1 clustering and weak lensing data with Baryon Acoustic Oscillations (BAO) and Big Bang Nucleosynthesis (BBN) experiments to constrain the Hubble constant. Assuming a flat $\Lambda$CDM model with minimal…

We compute the dynamical charge susceptibility in the two-dimensional Hubbard model within the dynamical cluster approximation. In order to understand the connection between charge susceptibility and pseudogap, we investigate the momentum,…