The LRT statistic converges in distribution to the supremum of a bar-chi-squared process under the null and a noncentral version under local alternatives, with the same form whether or not the information matrix is singular due to the nuisance parameter.
hub Mixed citations
The large-sample distribution of the likelihood ratio for testing composite hypotheses
Mixed citation behavior. Most common role is background (62%).
19
Pith papers citing it
Background
62% of classified citations
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method 3
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representative citing papers
Hidden birth event information restores identifiability to time-dependent birth-death phylodynamic models; mutation-at-birth models make sequences sufficient to recover it.
ScoreStop introduces a functional score test for early stopping in gradient boosting, testing the null that the current predictor minimizes population risk with a scale-invariant statistic of known asymptotic distribution.
DR-ME is the first semiparametrically efficient finite-location kernel test for interpretable distributional treatment effects, using orthogonal doubly robust features derived from observational data.
A QCD-vacuum-based model of dynamical dark energy fits Planck+ACT+SPT, DESI DR2, and supernova data while reproducing the late-time evolution favored by DESI.
DESI DR1 yields 314k high-mass and 9.6k dwarf AGN, extending the M_BH-M_star relation to log M_star ~7.8 and suggesting two evolutionary pathways for galaxies and black holes.
Six years of UV/X-ray monitoring of ESO 511-G030 reveals a >10x UV rise from the accretion disk, tight disk-corona coupling above ~1% Eddington, and breakdown below, indicating an accretion-state transition.
M-CaStLe generalizes local stencil-based causal discovery to the multivariate case and decomposes resulting graphs into reaction and spatial components for interpretation in space-time gridded data.
DAMPE independently detects the Fermi bubbles at 26 sigma and the Galactic center GeV excess at 7 sigma, with the excess spectrum and morphology matching Fermi-LAT and fitting a 50 GeV dark matter particle annihilating to b quarks.
RLAIF matches RLHF on summarization and dialogue tasks, with a direct-RLAIF variant achieving superior results by using LLM rewards directly during training.
A reweighting method creates model-agnostic likelihoods from histogram analyses, applied to Belle II B+ to K+ nu nubar data for WET constraints and light new physics searches.
For sub-GeV dark matter, the light and heavy mediator mass limits in direct detection are separated by up to three orders of magnitude in mediator mass, enabling precise sensitivity calculations for Si, Ge, and DAMIC-M targets.
Trajectory data resolves structural non-identifiability in lattice random walk diffusion models that count data alone cannot, with analysis of experimental design impacts on practical identifiability.
TeV gamma-ray optical depths yield a local EBL intensity consistent with integrated galaxy light to within 25% over 0.5-30 microns and incompatible at 3-5 sigma with near-IR excesses from IRTS and CIBER.
Updated constraints from the full Run 2 dataset show no evidence for anomalous Higgs couplings in gluon fusion, vector boson fusion, and associated production modes decaying to two photons.
Forecasts show that ~66 optical GRBs can achieve σ_w ≈ 0.47 in wCDM using Dainotti relations, matching Planck precision and enabling independent high-redshift tests of dark energy.
The reviewed method generalizes the Cash statistic C_min and likelihood-ratio ΔC to include systematic uncertainties in Poisson data, allowing simultaneous assessment of systematics level and model goodness-of-fit.
Develops a likelihood ratio framework for assessing highly motivated subdominant new physics signals against experimental residuals that appear consistent with background predictions.
citing papers explorer
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Semiparametric Efficient Test for Interpretable Distributional Treatment Effects
DR-ME is the first semiparametrically efficient finite-location kernel test for interpretable distributional treatment effects, using orthogonal doubly robust features derived from observational data.