Results 221 to 230 of about 390,909 (264)

Docking-based virtual screening: Past, present, and future. [PDF]

Biophys J
Xu X, Zou X.
europepmc   +1 more source

Learning Decouples Accuracy and Reaction Time for Rapid Decisions in a Transitive Inference Task. [PDF]

J Cogn Neurosci
Munoz F, Jensen G, Shinn M, Alkan Y, Murray JD, Terrace HS, Ferrera VP.   +6 more
europepmc   +1 more source

Reliability Assessment of Harmonic Reducers Based on the Two-Phase Hybrid Stochastic Degradation Process. [PDF]

Sensors (Basel)
Wei L, Liu P, Tian H, Li H, Qiu Y.
europepmc   +1 more source

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Classification by likelihood accordance functions

Communications in Statistics - Simulation and Computation, 2021
In this paper, we introduce the likelihood accordance function (LA function for short), which is defined to characterize the accordance of a new observation to be classified with training samples.
Yuqi Long, Xingzhong Xu
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On the Generalization of the Likelihood Function and the Likelihood Principle

Journal of the American Statistical Association, 1996
Abstract The parametric likelihood and likelihood principle (LP) play a central role in parametric methodology and in the foundations of statistics. The main purpose of this article is to extend the concepts of likelihood and LP to general inferential aims and models covering, for example, prediction and empirical Bayes models.
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A genotype likelihood function for DNA mixtures

Forensic Science International: Genetics, 2022
The recent advent of genetic genealogy has brought about a renewed interest in genome-scale forensic analyses, of which kinship estimation is a critical component. Most genomic kinship estimators consider SNPs (single nucleotide polymorphisms), often leveraging the co-inheritance of shared alleles to inform their analyses.
Benjamin, Crysup, August E, Woerner
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A reconfigurable architecture for the Phylogenetic Likelihood Function

2009 International Conference on Field Programmable Logic and Applications, 2009
As FPGA devices become larger, more coarse-grain modules coupled with large scale reconfigurable fabric become available, thus enabling new classes of applications to run efficiently, as compared to a general-purpose computer. This paper presents an architecture that benefits from the large number of DSP modules in Xilinx technology to implement ...
Nikolaos Alachiotis 0001, Alexandros Stamatakis, Euripides Sotiriades, Apostolos Dollas   +3 more
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Comparing the Likelihood Functions of Phylogenetic Trees

Annals of the Institute of Statistical Mathematics, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bar-Hen, A., Kishino, H.
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A projected likelihood function for semiparametric models

Biometrika, 1992
Summary: In a sequence of papers, the first author [Can J. Stat. 12, 265-282 (1984; Zbl 0574.62084)], \textit{J. E. Hutton} and \textit{P. I. Nelson} [Stochastic Processes Appl. 22, 245-257 (1986; Zbl 0616.62113)], and \textit{V. P. Godambe} and \textit{C. C. Heyde} [Int. Stat. Rev.
McLeish, D. L., Small, Christopher G.
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Assigning a Likelihood Function

2020
As scientists, we want to know how to parameterise our models, make comparisons with other models, and quantify model predictive uncertainty. For all these purposes, measurement data are needed, but how exactly should we use the data? The answer is always the same: in the likelihood function.
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