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"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-ignorable sampling, including outcome-dependent sampling. The new designs have probabilities of selection closely related to influence statistics such as dfbeta and Cook's distance. The new approach is shown to perform well in a simulation based on data from the New Zealand Health Survey. ....

New Zealand , Zealand Health , New Zealand Health , Design Based , Maximum Likelihood , Model Assisted , Poisson Sampling , Seudo Likelihood , Sample Design , Tratified Sampling ,

Taxonomic complexity of Sambucus genus studied

Taxonomic complexity of Sambucus genus studied
miragenews.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from miragenews.com Daily Mail and Mail on Sunday newspapers.

Sambucusl Viburnaceae , National Natural Science Foundation Of China , Research Center , Wuhan Botanical Garden , Chinese Academy , Maximum Likelihood , National Natural Science Foundation , Sino Africa Joint Research Center ,

Human-level play in the game of Diplomacy by combining language models with strategic reasoning

Human-level play in the game of Diplomacy by combining language models with strategic reasoning
science.org - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from science.org Daily Mail and Mail on Sunday newspapers.

North Sea , Oceans General , Kestas Kuliukas , Kurt Shuster , Jacob Andreas , Jason Weston , Susan Zhang , Philip Paquette , Maximum Likelihood , Distributional Lambda , Yet Cicero , Naman Goyal ,