Results 71 to 80 of about 1,934,057 (295)
Evidential Estimation of an Uncertain Mixed Exponential Distribution under Progressive Censoring
Entropy, 2020 In this paper, the evidential estimation method for the parameters of the mixed exponential distribution is considered when a sample is obtained from Type-II progressively censored data.
Kuang Zhou, Yimin Shi
doaj +1 more source
Split Sample Empirical Likelihood [PDF]
arXiv, 2017 We propose a new approach that combines multiple non-parametric likelihood-type components to build a data-driven approximation of the true likelihood function. Our approach is built on empirical likelihood, a non-parametric approximation of the likelihood function.
arxiv
Statistical inference of random graphs with a surrogate likelihood function [PDF]
arXiv, 2022 Spectral estimators have been broadly applied to statistical network analysis but they do not incorporate the likelihood information of the network sampling model. This paper proposes a novel surrogate likelihood function for statistical inference of a class of popular network models referred to as random dot product graphs.
arxiv
Identification of novel small molecule inhibitors of ETS transcription factors
FEBS Letters, EarlyView.ETS transcription factors play an essential role in tumourigenesis and are indispensable for sprouting angiogenesis, a hallmark of cancer, which fuels tumour expansion and dissemination. Thus, targeting ETS transcription factor function could represent an effective, multifaceted strategy to block tumour growth. The evolutionarily conserved E‐Twenty‐Six
Shaima Abdalla +9 more
wiley +1 more source
Maximum Likelihood for Matrices with Rank Constraints [PDF]
, 2013 Maximum likelihood estimation is a fundamental optimization problem in statistics. We study this problem on manifolds of matrices with bounded rank. These represent mixtures of distributions of two independent discrete random variables.
Hauenstein, Jonathan +2 more
core
Journal of Statistical Software, 2016 The statistical analysis of circular, multivariate circular, and spherical data is very important in different areas, such as paleomagnetism, astronomy and biology.
Juan José Fernández-Durán +1 more
doaj +1 more source
Maximum likelihood degree of Fermat hypersurfaces via Euler characteristics [PDF]
arXiv, 2015 Maximum likelihood degree of a projective variety is the number of critical points of a general likelihood function. In this note, we compute the Maximum likelihood degree of Fermat hypersurfaces. We give a formula of the Maximum likelihood degree in terms of the constants $\beta_{\mu, \nu}$, which is defined to be the number of complex solutions to ...
arxiv
FEBS Letters, EarlyView.In lymphoid organs, antigen recognition and B cell receptor signaling rely on integrins and the cytoskeleton. Integrins act as mechanoreceptors, couple B cell receptor activation to cytoskeletal remodeling, and support immune synapse formation as well as antigen extraction.
Abhishek Pethe, Tanja Nicole Hartmann
wiley +1 more source
Likelihood Consensus and Its Application to Distributed Particle Filtering
, 2012 We consider distributed state estimation in a wireless sensor network without a fusion center. Each sensor performs a global estimation task---based on the past and current measurements of all sensors---using only local processing and local ...
Djuric, Petar M. +4 more
core +1 more source
Generalized Topp-Leone family of distributions
Journal of Biostatistics and Epidemiology, 2018 Background & Aim: Adding parameters to an existing distribution to expand the family of distributions is a very common approach for developing more flexible models.
Abbas Mahdavi
doaj