"Poisson Distribution" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
A distribution function used to describe the occurrence of rare events or to describe the sampling distribution of isolated counts in a continuum of time or space.
Below are MeSH descriptors whose meaning is more general than "Poisson Distribution".
Below are MeSH descriptors whose meaning is more specific than "Poisson Distribution".
This graph shows the total number of publications written about "Poisson Distribution" by people in this website by year, and whether "Poisson Distribution" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
|Year||Major Topic||Minor Topic||Total|
To return to the timeline, click here.
Below are the most recent publications written about "Poisson Distribution" by people in Profiles.
Participation in the Child and Adult Care Food Program is associated with fewer barriers to serving healthier foods in early care and education. BMC Public Health. 2020 Jun 05; 20(1):856.
An extended proportional hazards model for interval-censored data subject to instantaneous failures. Lifetime Data Anal. 2020 01; 26(1):158-182.
Low Rate of Return to Impact Activity Following Core Decompression for Femoral Head AVN in Military Servicemembers. Mil Med. 2019 01 01; 184(1-2):e243-e248.
BioSimulator.jl: Stochastic simulation in Julia. Comput Methods Programs Biomed. 2018 Dec; 167:23-35.
A partially linear proportional hazards model for current status data. Biometrics. 2018 12; 74(4):1240-1249.
An assessment of the CHIP/Medicaid quality measure for ADHD. Am J Manag Care. 2017 Jan 01; 23(1):e1-e9.
Disease mapping of zero-excessive mesothelioma data in Flanders. Ann Epidemiol. 2017 Jan; 27(1):59-66.e3.
Space-time variation of respiratory cancers in South Carolina: a flexible multivariate mixture modeling approach to risk estimation. Ann Epidemiol. 2017 Jan; 27(1):42-51.
Modeling excess zeros and heterogeneity in count data from a complex survey design with application to the demographic health survey in sub-Saharan Africa. Stat Methods Med Res. 2018 01; 27(1):208-220.
The LZIP: A Bayesian latent factor model for correlated zero-inflated counts. Biometrics. 2017 03; 73(1):185-196.