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"The missing information principle ‒ A paradigm for analysis of messy s" by Raymond L. Chambers

Sample surveys, as a tool for policy development and evaluation and for scientific, social and economic research, have been employed for over a century. In that time, they have primarily served as tools for collecting data for enumerative purposes. Estimation of these characteristics has been typically based on weighting and repeated sampling, or design-based, inference. However, sample data have also been used for modelling the unobservable processes that gave rise to the finite population data...
Missing Information Principle Combined Data Nformative Sampling Maximum Likelihood Ondeterministic Linkage Small Area Estimation
Source: uow.edu.au

Yeast species used in food industry causes disease in humans

Public Release: 19-Jul-2018PLOSCaptionA phylogenetic tree of strains was constructed from data from a filtered set of 150,306 SNP sites, using RRHS and Maximum Likelihood (see Methods). Branch supports represent pseudo-bootstrap values. Strains named in red are clinical isolates, and strains named in blue are environmental. For each strain, four circles indicate relative resistance (magenta) or…
Ken Wolfe Alexander Douglass University College Dublin Public Release Maximum Likelihood Professor Ken Wolfe

"Sample design for analysis using high-influence probability sampling" by Robert G. Clark and David G. Steel

Sample designs are typically developed to estimate summary statistics such as means, proportions and prevalences. Analytical outputs may also be a priority but there are fewer methods and results on how to efficiently design samples for the fitting and estimation of statistical models. This paper develops a general approach for determining efficient sampling designs for probability-weighted maximum likelihood estimators and considers application to generalized linear models. We allow for non-ign...
New Zealand Zealand Health New Zealand Health Design Based Maximum Likelihood Model Assisted
Source: uow.edu.au

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Enterovirus detection in different regions of Madagascar reveals a higher abundance of enteroviruses of species C in areas where several outbreaks of vaccine-derived polioviruses occurred | BMC Infectious Diseases

Poliomyelitis outbreaks due to pathogenic vaccine-derived polioviruses (VDPVs) are threatening and complicating the global polio eradication initiative. Most of these VDPVs are genetic recombinants with non-polio enteroviruses (NPEVs) of species C. Little is known about factors favoring this genetic macroevolution process. Since 2001, Madagascar has experienced several outbreaks of poliomyelitis due to VDPVs, and most of VDPVs were isolated in the south of the island. The current study explored ...
United Kingdom Languedoc Roussillon Beckman Coulter Genomics Company Genewiz Global Polio Laboratory Network Modified Eagle Medium Polio Laboratory Network

Vulnerability as an Ex Ante Measure of Poverty : An Empirical Investigation for India

Using both rounds of the India Human Development Survey, vulnerability is measured as an ex ante measure of poverty for the Indian households. This article highlights the importance of measuring vulnerability in the overall poverty calculation and found it to be a significant predictor of the future poverty.
New York United States United Kingdom New Delhi Republic Of Columbia University
Source: epw.in

"Spherical Poisson point process intensity function modeling and estima" by Tin Lok James Ng and Andrew Zammit-Mangion

Recent years have seen an increased interest in the application of methods and techniques commonly associated with machine learning and artificial intelligence to spatial statistics. Here, in a celebration of the ten-year anniversary of the journal Spatial Statistics, we bring together normalizing flows, commonly used for density function estimation in machine learning, and spherical point processes, a topic of particular interest to the journal's readership, to present a new approach for m...
Pacific Ocean Spatial Statistics North Pacific Exponential Map Maximum Likelihood Normalizing Flows
Source: uow.edu.au

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