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The Dirichlet-multinomial (DM) distribution plays a fundamental role in modern statistical methodology development and application. Recently, the DM distribution and its variants have been used extensively to model multivariate count data…

Methodology · Statistics 2023-02-27 Matthew D. Koslovsky

We go through the many considerations involved in fitting a model to data, using as an example the fit of a straight line to a set of points in a two-dimensional plane. Standard weighted least-squares fitting is only appropriate when there…

Instrumentation and Methods for Astrophysics · Physics 2010-08-30 David W. Hogg , Jo Bovy , Dustin Lang

In classical density (or density-functional) estimation, it is standard to assume that the underlying distribution has a density with respect to the Lebesgue measure. However, when the data distribution is a mixture of continuous and…

Methodology · Statistics 2025-08-05 Aytijhya Saha , Aaditya Ramdas

We investigate the effect of extending the standard MSTW parameterisation of input parton distribution functions (PDFs) using Chebyshev polynomials. We find evidence that four powers in the polynomial are sufficient for extremely high…

High Energy Physics - Phenomenology · Physics 2013-03-18 A. D. Martin , A. J. Th. M. Mathijssen , W. J. Stirling , R. S. Thorne , B. J. A. Watt , G. Watt

We scrutinize the recent LHCb data for D$^0$-meson production in p+Pb collisions within a next-to-leading order QCD framework. Our calculations are performed in the SACOT-$m_{\rm T}$ variant of the general-mass variable-flavour-number…

High Energy Physics - Phenomenology · Physics 2020-06-24 Kari J. Eskola , Ilkka Helenius , Petja Paakkinen , Hannu Paukkunen

In the analysis of survey data, sampling weights are needed for consistent estimation of the population. However, the original inverse probability weights from the survey sample design are typically modified to account for non-response, to…

Computation · Statistics 2025-08-19 Matthew R. Williams , Terrance D. Savitsky

Compositional data, representing proportions constrained to the simplex, arise in diverse fields such as geosciences, ecology, genomics, and microbiome research. Existing nonparametric density estimation methods often rely on…

Methodology · Statistics 2025-10-10 Jiajin Xie , Yong Wang , Eduardo García-Portugués

Distance-based regression model, as a nonparametric multivariate method, has been widely used to detect the association between variations in a distance or dissimilarity matrix for outcomes and predictor variables of interest in genetic…

Statistics Theory · Mathematics 2022-03-14 Yuke Shi , Wei Zhang , Aiyi Liu , Qizhai Li

The results on polarized parton densities (PDFs) obtained using different methods of QCD analysis of the present polarized DIS data are discussed. Their dependence on the method used in the analysis, accounting or not for the kinematic and…

High Energy Physics - Phenomenology · Physics 2009-11-05 Elliot Leader , Aleksander V. Sidorov , Dimiter B. Stamenov

We investigate the parton distribution function (PDF) uncertainty in the measurement of the effective weak mixing angle $\sin^2\theta_{\text{eff}}^{\ell}$ at the CERN Large Hadron Collider (LHC). The PDF-induced uncertainty is large in the…

High Energy Physics - Experiment · Physics 2021-05-26 Yao Fu , Siqi Yang , Minghui Liu , Liang Han , Tie-Jiun Hou , Carl Schmidt , Chen Wang , C. -P. Yuan

Learning in deep weight spaces (DWS), where neural networks process the weights of other neural networks, is an emerging research direction, with applications to 2D and 3D neural fields (INRs, NeRFs), as well as making inferences about…

Machine Learning · Computer Science 2024-11-12 Aviv Shamsian , Aviv Navon , David W. Zhang , Yan Zhang , Ethan Fetaya , Gal Chechik , Haggai Maron

Estimating causal effects from observational data is challenging due to selection bias, which leads to imbalanced covariate distributions across treatment groups. Propensity score-based weighting methods are widely used to address this…

Machine Learning · Computer Science 2025-08-08 Ahmad Saeed Khan , Erik Schaffernicht , Johannes Andreas Stork

Despite the remarkable generation capabilities of Diffusion Models (DMs), conducting training and inference remains computationally expensive. Previous works have been devoted to accelerating diffusion sampling, but achieving data-efficient…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Yize Li , Yihua Zhang , Sijia Liu , Xue Lin

Parton distribution functions (PDFs) at large $x$ are poorly constrained by high-energy experimental data, but extremely important for probing physics beyond standard model at colliders. We study the calculation of PDFs at large-$x$ through…

High Energy Physics - Phenomenology · Physics 2025-08-05 Xiangdong Ji , Yizhuang Liu , Yushan Su

We study the impact of differential isolated-photon+jet cross sections measured in proton-proton collisions at a center-of-mass energy of sqrt{s} = 7 TeV on the parton distribution functions (PDF) of the proton. Next-to-leading order…

High Energy Physics - Phenomenology · Physics 2015-06-12 L. Carminati , G. Costa , D. d'Enterria , I. Koletsou , G. Marchiori , J. Rojo , M. Stockton , F. Tartarelli

We present recent results of the NNPDF collaboration on a full DIS analysis of Parton Distribution Functions (PDFs). Our method is based on the idea of combining a Monte Carlo sampling of the probability measure in the space of PDFs with…

High Energy Physics - Phenomenology · Physics 2008-05-21 NNPDF Collaboration , M. Ubiali , R. D. Ball , L. Del Debbio , S. Forte , A. Guffanti , J. I. Latorre , A. Piccione , J. Rojo

We present NNPDF3.0, the first set of parton distribution functions (PDFs) determined with a methodology validated by a closure test. NNPDF3.0 uses a global dataset including HERA-II deep-inelastic inclusive cross-sections, the combined…

We present a model for inclusive charged lepton-nucleon and (anti)neutrino-nucleon cross sections at momentum transfer squared, $Q^2$, $\sim1 {\rm GeV}^2$. We quantify the impact of existing low-Q charged-lepton deep-inelastic scattering…

High Energy Physics - Phenomenology · Physics 2014-11-18 S. Alekhin , S. A. Kulagin , R. Petti

We gauge the impact of soft-gluon resummation on quark distributions by performing a simple fit of Deep Inelastic Scattering structure function data using next-to-leading order (NLO) and next-to-leading-logarithmic (NLL)-resummed…

High Energy Physics - Phenomenology · Physics 2009-11-11 Gennaro Corcella , Lorenzo Magnea

We present a determination of the parton distributions of the nucleon from a global set of hard scattering data using the NNPDF methodology at LO and NNLO in perturbative QCD, thereby generalizing to these orders the NNPDF2.1 NLO parton…