A Nonparametric Bayesian Approach to the Rare Type Match Problem
Entropy, 2020 The “rare type match problem” is the situation in which, in a criminal case, the suspect’s DNA profile, matching the DNA profile of the crime stain, is not in the database of reference.
Giulia Cereda, Richard D. Gill
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Integration based profile likelihood calculation for PDE constrained parameter estimation problems [PDF]
, 2016 Partial differential equation (PDE) models are widely used in engineering and natural sciences to describe spatio-temporal processes. The parameters of the considered processes are often unknown and have to be estimated from experimental data.
R Boiger +3 more
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Hierarchical Generalized Linear Models: The R Package HGLMMM [PDF]
Journal of Statistical Software, 2011 The R package HGLMMM has been developed to fit generalized linear models with random effects using the h-likelihood approach. The response variable is allowed to follow a binomial, Poisson, Gaussian or gamma distribution.
Marek Molas, Emmanuel Lesaffre
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Decaying dark matter with profile likelihoods [PDF]
Physical Review D, 2023 A large number of studies, all using Bayesian parameter inference from Markov chain Monte Carlo methods, have constrained the presence of a decaying dark matter component. All such studies find a strong preference for either very long-lived or very short-lived dark matter.
Emil Brinch Holm +4 more
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Profile Likelihood and Incomplete Data. [PDF]
Int Stat Rev, 2010 Summary According to the law of likelihood, statistical evidence is represented by likelihood functions and its strength measured by likelihood ratios. This point of view has led to a likelihood paradigm for interpreting statistical evidence, which carefully distinguishes evidence about a parameter from error probabilities and personal belief.
Zhang Z.
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PROSPECT: A profile likelihood code for frequentist cosmological parameter inference [PDF]
Monthly notices of the Royal Astronomical Society, 2023 Cosmological parameter inference has been dominated by the Bayesian approach for the past two decades, primarily due to its computational efficiency. However, the Bayesian approach involves integration of the posterior probability and therefore depends
Emil Brinch Holm +4 more
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The failure of the profile likelihood method for a large class of semi-parametric models [PDF]
, 2017 Eric Beutner +2 more
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New Constraint on Early Dark Energy from Planck and BOSS Data Using the Profile Likelihood [PDF]
Astrophysical Journal Letters, 2021 A dark energy–like component in the early universe, known as early dark energy (EDE), is a proposed solution to the Hubble tension. Currently, there is no consensus in the literature as to whether EDE can simultaneously solve the Hubble tension and ...
Laura Herold +2 more
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New Constraint on the Tensor-to-scalar Ratio from the Planck and BICEP/Keck Array Data Using the Profile Likelihood [PDF]
Astrophysical Journal, 2022 Motivated by the discrepancy between Bayesian and frequentist upper limits on the tensor-to-scalar ratio parameter r found by the SPIDER collaboration, we investigate whether a similar trend is also present in the latest Planck and BICEP/Keck Array data.
P. Campeti, E. Komatsu
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A generalized Liu-type estimator for logistic partial linear regression model with multicollinearity
AIMS Mathematics, 2023 This paper is concerned with proposing a generalized Liu-type estimator (GLTE) to address the multicollinearity problem of explanatory variable of the linear part in the logistic partially linear regression model.
Dayang Dai , Dabuxilatu Wang
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