Results 231 to 240 of about 2,194,170 (284)

Application of Bayesian statistics to estimate nitrous oxide emission factors of three nitrogen fertilisers on UK grasslands.

Environ Int, 2019
Cowan N, Levy P, Drewer J, Carswell A, Shaw R, Simmons I, Bache C, Marinheiro J, Brichet J, Sanchez-Rodriguez AR, Cotton J, Hill PW, Chadwick DR, Jones DL, Misselbrook TH, Skiba U.   +15 more
europepmc   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Advanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source

Bayesian Modeling of Bovine Tuberculosis Prevalence for Enhanced Estimation and Control in Intensive Dairy Farms: A Longitudinal Decision-Support Tools for Veterinarians and Policymakers. [PDF]

Vet Med Int
Abera B, Gumi B, Ameni G, Smith RL, Mamo G.   +4 more
europepmc   +1 more source

A Guide for Exploring Pleiotropic Associations in Genome-Wide Association Studies Using Summary Statistics. [PDF]

Stat Med
Feng CY, Sugier PE, Zou N, Liquet B.
europepmc   +1 more source

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The Development of Bayesian Statistics

Journal of the Indian Institute of Science, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Overview of Bayesian Statistics

Evaluation Review, 2020
Bayesian statistics is becoming a popular approach to handling complex statistical modeling. This special issue of Evaluation Review features several Bayesian contributions. In this overview, I present the basics of Bayesian inference. Bayesian statistics is based on the principle that parameters have a distribution of beliefs about them that behave ...
openaire   +2 more sources

Bayesian statistics for parasitologists

Trends in Parasitology, 2004
Bayesian statistical methods are increasingly being used in the analysis of parasitological data. Here, the basis of differences between the Bayesian method and the classical or frequentist approach to statistical inference is explained. This is illustrated with practical implications of Bayesian analyses using prevalence estimation of strongyloidiasis
María-Gloria, Basáñez, Clare, Marshall, Hélène, Carabin, Theresa, Gyorkos, Lawrence, Joseph   +4 more
openaire   +2 more sources

Understanding Bayesian Statistics

Journal of Spinal Disorders & Techniques, 2015
Modern computing power has given us the ability to approach statistical questions in a manner which was previously impossible because of the time-consuming nature of the calculations required. Computer power has enabled the use of Bayesian inference techniques, based on 18th century theory, to frame statistical questions in probability.
openaire   +2 more sources