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, 2020 We study the significance of non-Gaussianity in the likelihood of weak lensing shear two-point correlation functions, detecting significantly non-zero skewness and kurtosis in one-dimensional marginal distributions of shear two-point correlation ...
Eifler, Tim +6 more
core +1 more source
Testable likelihoods for beyond-the-standard model fits
European Physical Journal C: Particles and Fields, 2023 Studying potential BSM effects at the precision frontier requires accurate transfer of information from low-energy measurements to high-energy BSM models.
Anja Beck, Méril Reboud, Danny van Dyk
doaj +1 more source
Jeffreys-prior penalty, finiteness and shrinkage in binomial-response generalized linear models [PDF]
, 2020 Penalization of the likelihood by Jeffreys' invariant prior, or by a positive power thereof, is shown to produce finite-valued maximum penalized likelihood estimates in a broad class of binomial generalized linear models.
Firth, David, Kosmidis, Ioannis
core +2 more sources
Composite Likelihood Inference by Nonparametric Saddlepoint Tests [PDF]
, 2013 The class of composite likelihood functions provides a flexible and powerful toolkit to carry out approximate inference for complex statistical models when the full likelihood is either impossible to specify or unfeasible to compute.
Lunardon, Nicola, Ronchetti, Elvezio
core +4 more sources
Renormalization group computation of likelihood functions for cosmological data sets [PDF]
, 2018 I show how a renormalization group (RG) method can be used to incrementally integrate the information in cosmological large-scale structure data sets (including CMB, galaxy redshift surveys, etc.).
McDonald, Patrick
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The Analysis of Ranking Data Using Score Functions and Penalized Likelihood
Austrian Journal of Statistics, 2017 In this paper, we consider different score functions in order summarize certain characteristics for one and two sample ranking data sets. Our approach is flexible and is based on embedding the nonparametric problem in a parametric framework.
Mayer Alvo, Hang Xu
doaj +1 more source
Copula cosmology: Constructing a likelihood function [PDF]
Physical Review D, 2011 To estimate cosmological parameters from a given dataset, we need to construct a likelihood function, which sometimes has a complicated functional form. We introduce the copula, a mathematical tool to construct an arbitrary multivariate distribution function from one-dimensional marginal distribution functions with any given dependence structure. It is
Sato, Masanori +2 more
openaire +2 more sources
New developments in the ROOT fitting classes [PDF]
EPJ Web of Conferences, 2019 The ROOT Mathematical and Statistical libraries have been recently improved both to increase their performance and to facilitate the modelling of parametric functions that can be used for performing maximum likelihood fits to data sets to estimate ...
Valls Xavier +3 more
doaj +1 more source
The Annals of Statistics, 1983 The connection between quasi-likelihood functions, exponential family models and nonlinear weighted least squares is examined. Consistency and asymptotic normality of the parameter estimates are discussed under second moment assumptions. The parameter estimates are shown to satisfy a property of asymptotic optimality similar in spirit to, but more ...
openaire +3 more sources
Occupational stress and body composition of hospital workers: a follow-up study
Frontiers in Public HealthThis study sought to analyze the influence of occupational stress on the body composition of hospital workers after one year of follow-up. This prospective cohort study included 218 workers from one of the leading private hospitals in the municipality of
Carlos Rodrigo Nascimento de Lira +4 more
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