Likelihood inference in the presence of nuisance parameters [PDF]
arXiv, 2003 We describe some recent approaches to likelihood based inference in the presence of nuisance parameters. Our approach is based on plotting the likelihood function and the $p$-value function, using recently developed third order approximations. Orthogonal parameters and adjustments to profile likelihood are also discussed.
arxiv
Ion channel function of polycystin‐2/polycystin‐1 heteromer revealed by structure‐guided mutagenesis
FEBS Letters, EarlyView.Mutations in polycystin‐1 (PC1) or polycystin‐2 (PC2) cause autosomal‐dominant polycystic kidney disease (ADPKD). We generated a novel gain‐of‐function PC2/PC1 heteromeric ion channel by mutating pore‐blocking residues. Moreover, we demonstrated that PC2 will preferentially assemble with PC1 to form heteromeric complexes when PC1 is co‐expressed ...
Tobias Staudner +7 more
wiley +1 more source
Making Likelihood Calculations Fast: Automatic Differentiation Applied to RooFit [PDF]
EPJ Web of ConferencesWith the growing datasets of current and next-generation HighEnergy and Nuclear Physics (HEP/NP) experiments, statistical analysis has become more computationally demanding.
Singh Garima +4 more
doaj +1 more source
sFit: a method for background subtraction in maximum likelihood fit [PDF]
arXiv, 2009 This paper presents a statistical method to subtract background in maximum likelihood fit, without relying on any separate sideband or simulation for background modeling. The method, called sFit, is an extension to the sPlot technique originally developed to reconstruct true distribution for each date component.
arxiv
Autophagy in cancer and protein conformational disorders
FEBS Letters, EarlyView.Autophagy plays a crucial role in numerous biological processes, including protein and organelle quality control, development, immunity, and metabolism. Hence, dysregulation or mutations in autophagy‐related genes have been implicated in a wide range of human diseases.
Sergio Attanasio
wiley +1 more source
Wasserstein metric-driven Bayesian inversion with applications to signal processing [PDF]
arXiv, 2018 We present a Bayesian framework based on a new exponential likelihood function driven by the quadratic Wasserstien metric. Compared to conventional Bayesian models based on Gaussian likelihood functions driven by the least-squares norm ($L_2$ norm), the new framework features several advantages.
arxiv
FEBS Letters, EarlyView.The protonated form of butyrate, as well as other short‐chain fatty acids (SCFAs), is membrane permeable. In acidic extracellular environments, this can lead to intracellular accumulation of SCFAs and cytosolic acidification. This phenomenon will be particularly relevant in acidic environments such as the large intestine or tumor microenvironments ...
Muwei Jiang +2 more
wiley +1 more source
An 'average information' restricted maximum likelihood algorithm for estimating reduced rank genetic covariance matrices or covariance functions for animal models with equal design matrices [PDF]
, 1997 Karin Meyer
openalex +3 more sources
An investigation into the Multiple Optimised Parameter Estimation and Data compression algorithm
, 2011 We investigate the use of the Multiple Optimised Parameter Estimation and Data compression algorithm (MOPED) for data compression and faster evaluation of likelihood functions.
Anthony Lasenby +6 more
core +1 more source
Reliable inference for complex models by discriminative composite likelihood estimation [PDF]
arXiv, 2015 Composite likelihood estimation has an important role in the analysis of multivariate data for which the full likelihood function is intractable. An important issue in composite likelihood inference is the choice of the weights associated with lower-dimensional data sub-sets, since the presence of incompatible sub-models can deteriorate the accuracy of
arxiv