... Parameter-dependent support MPEC Flexible parametric form Approximate profile likelihood-ratio Bayes credible sets Frequentist confidence sets Risk aversion and entry are both important considerations in real-world auction markets. Unfortunately, the interaction between these factors also raises...

...-average molecular weights (Mn), and PDI value of 79 propellants samples from different sources were measured by gel permeation chromatography, and likelihood ratio evaluation method was applied to facilitate interpretation of the data. The possibility of using these methods to make comparisons between...

...Ronald Brent Ostrum Abstract With various calls in the forensic scientific literature for pattern-matching disciplines to adopt evaluative reporting, which is also known as the likelihood ratio or logical approach, practitioners used to reporting evidence under a more traditional paradigm may have...

... of cumulative sum-based change-point tests in the context of a random coefficient autoregressive model of order 1. In the current paper, we complement the results in that contribution by studying the (maximally selected) likelihood ratio statistic. We show that this has power versus breaks occurring even...

...Parham Boroumand; Albert Guillén i Fàbregas (2.3) where . It is well known that likelihood ratio test defined as (2.4) attains the optimal tradeoff ( 2.3 ) for every . This is the well-known Neyman–Pearson lemma [ 30 ]. The likelihood ratio test can also be expressed as a function of the type...

...Geoffrey Stewart Morrison Figure 2. (a) Different-source and same-source Gaussian distributions with, μ d = - 4.5 , μ s = 4.5 , σ = 3 . (b) Log-likelihood-ratio-to-log-likelihood-ratio mapping function corresponding to (a). (c) Different-source and same...

... problematic part of Bayesian reasoning. We explain that attempts to numerically express the prior fail in general, but also that a prior is necessary and cannot be dispensed with. Indeed, we explain in detail why decision-making should not be based on likelihood ratios alone. We next discuss two of the most...

... to summary statistics from a genome-wide association study (GWAS) and a reference panel of genotype data. Besides estimation, a distinct feature of the method is its summary statistics-based likelihood ratio test on directed edges. We applied our method to estimate a causal network of 29 cardiovascular...

... the generalization gap considering the mismatch of testing on the accuracy metric and training on the negative log-loss, referred to as PACMAN. Building on the fact that the resulting mismatch can be written as a likelihood ratio, concentration inequalities can be used to obtain insights into the generalization gap...

... forensic scientists, forensic statisticians, lawyers, judges, and prosecutors, are considering the statistical model based on the likelihood ratio (LR) method as one of the most accurate and logical frameworks for assessing forensic evidence [ 19–22 ]. LR is a statistical method used to weigh the probative...

.... In this paper, we establish large-sample properties of the maximum likelihood estimator when the true parameter value lies at the boundary of a nonconvex parameter space. We further derive the asymptotic distribution of the likelihood ratio test statistic under nonconvex constraints on model parameters...

... elaborate forms of blocking in an experimental context, or models for longitudinal or clustered data. The salient point, echoing Dickey (2020) , is that a suitable likelihood-ratio test should always be used for the assessment of variance components. Components of variance Likelihood ratio Nuisance...

... t 2 have a common, unknown source, or whether they have different sources. This article studies expected performance and practical feasibility of the most commonly used classes of source-level likelihood-ratio (LR) systems when applied to a trace–reference comparison problem. The article...

... in the identification of new targets and the quantification of the prevalence of balancing selection, thus enhancing our understanding of its role in natural populations. natural selection population genomics summary statistics composite likelihood ratio tests genetic variation heterozygote advantage São Paulo...

... Geweke introduced the standard vector-autoregressive, var, formalism, and the Granger–Geweke population loglikelihood ratio statistic ( Geweke, 1982 , 1984 ). As well as furnishing a likelihood ratio test for statistical significance, the statistic has been shown to have an intuitive...

... the likelihood ratio approach and formulate the linear response as a product of two martingales, hence the name ‘martingale product estimators’. We present a systematic derivation of the martingale product estimator, and show how to construct such estimator so that its bias is consistent with the weak order...

..., concerning the expected likelihood ratio in forensic kinship testing, and variances in realized relatedness. pairwise relatedness identity-by-descent identity coefficients kinship pedigree analysis two-locus coefficients expected likelihood ratio realized relatedness linkage Norwegian Research...

...Jȩdrzej Wydra; Szymon Matuszewski Email: [email protected] 14 11 2022 We have chosen to use beta probability distribution to calculate probabilities for both the numerator and the denominator of our likelihood ratio because the support of this distribution is an interval [ 0 , 1...

... into discrete categories. Motivated by certain features of these curves, we introduce a powerful likelihood ratio approach to construct confidence bands and compare functional means. Notably, our approach allows discontinuities in the functional covariances while accommodating discretization of the observed...

... and derive its representer theorem. The rate of convergence, a Bahadur representation, and the asymptotic pointwise distribution of the functional estimator are obtained under the reproducing kernel Hilbert space framework. We propose a penalized likelihood ratio test to test the nullity of the functional...