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An Evaluation of Soil Test Information in Agricultural Decision Making AgEcon
Babcock, Bruce A.; Carriquiry, Alicia L.; Stern, Hal S..
The value of soil-test information in planning fertilizer application levels is determined by using agricultural field-plot data to estimate the posterior distribution of mean soil-nitrate concentrations at a give location. Optimal decisions concerning fertilizer application levels are made with respect to this posterior distribution. Average reductions in fertilizer application rates range from 15 to 41 percent, depending on the form of prior information that is available. These reductions are achieved by increasing the variability of application rates over time. Disregarding the uncertainty that remains after the soil testing significantly overstates the expected benefits of soil testing.
Tipo: Working or Discussion Paper Palavras-chave: Bayesian methods; Fertilizer rates; Posterior distributions; Soil tests; Farm Management.
Ano: 1996 URL: http://purl.umn.edu/18633
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Bayesian analysis in Stata with WinBUGS AgEcon
Thompson, John M.; Palmer, Tom M.; Moreno, Santiago G..
WinBUGS is a program for Bayesian model fitting by Gibbs sampling. WinBUGS has limited facilities for data handling, whereas Stata has no routines for Bayesian analysis; therefore, much can be gained by running Stata and WinBUGS together. We present a set of ado-files that enable data to be processed in Stata and then passed to WinBUGS for model fitting; finally, the results are read back into Stata for further processing.
Tipo: Article Palavras-chave: Wbarray; Wbdata; Wbscalar; Wbstructure; Wbvector; Wbrun; Wbscript; Wbcoda; Wbac; Wbbgr; Wbgeweke; Wbintervals; Wbsection; Wbtrace; Wbstats; Wbdensity; Wbdic; Wbbull; Wbdecode; Bayesian methods; MCMC; Gibbs sampling; WinBUGS; Research Methods/ Statistical Methods.
Ano: 2006 URL: http://purl.umn.edu/119243
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Mixture models in quantitative genetics and applications to animal breeding R. Bras. Zootec.
Gianola,Daniel; Boettcher,Paul J.; Ødegård,Jørgen; Heringstad,Bjørg.
Finite mixture models are helpful for uncovering heterogeneity due to hidden structure; for example, unknown major genes. The first part of this article gives examples and reviews quantitative genetics issues of continuous characters having a finite mixture of Gaussian components. The partition of variance in a mixture, the covariance between relatives under the supposition of an additive genetic model and the offspring-parent regression are derived. Formulae for assessing the effect of mass selection operating on a mixture are given. Expressions for the genetic correlation between a mixture and a Gaussian trait are presented. If there is heterogeneity in a population at the genetic or environmental levels, then genetic parameters based on theory treating...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Bayesian methods; Dairy cattle; Maximum likelihood; Mixture distributions; Quantitative genetics; Somatic cell scores.
Ano: 2007 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982007001000017
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Ridge, Lasso and Bayesian additive dominance genomic models. Repositório Alice
AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F. e; VIANA, J. M. S.; VALENTE, M. S. F.; RESENDE JUNIOR, M. F. R.; MUÑOZ, P..
Background: A complete approach for genome-wide selection (GWS) involves reliable statistical genetics models and methods. Reports on this topic are common for additive genetic models but not for additive-dominance models. The objective of this paper was (i) to compare the performance of 10 additive-dominance predictive models (including current models and proposed modifications), fitted using Bayesian, Lasso and Ridge regression approaches; and (ii) to decompose genomic heritability and accuracy in terms of three quantitative genetic information sources, namely, linkage disequilibrium (LD), co-segregation (CS) and pedigree relationships or family structure (PR). The simulation study considered two broad sense heritability levels (0.30 and 0.50, associated...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Modelo Bayesiano; Genética quantitativa; Melhoramento genético; Parâmetro genético; Dominance genomic models; Bayesian methods; Lasso methods; Selection accuracy.
Ano: 2015 URL: http://www.alice.cnptia.embrapa.br/handle/doc/1022575
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Stock assessment of the English Channel stock of cuttlefish with a two-stage biomass model ArchiMer
Alemany, Juliette; Foucher, Eric; Rivot, Etienne; Vigneau, Joel; Robin, Jean-paul.
Among the English Channel fishery, the importance of cuttlefish stock has increased, following the cephalopods global landings and market trend. The stock is currently managed at regional scale but not by European regulations, although it is a shared species targeted by French and British fishing fleets at several stages of its life-cycle and across much of its distributional range. An assessment of this stock was conducted in June 2014 by fitting a two-stage biomass model on a 22 years’ time-series (1992-2013). We present the last update of cuttlefish stock assessment using the same model on years 1992-2014. As the outputs of the model are sensitive to a fix growth parameter, we explore possibilities to improve the model. The use of a Bayesian framework...
Tipo: Text Palavras-chave: Stock assessment; Short-lived species; Data-limited; Cuttlefish; Sepia officinalis; English Channel; Two-stage biomass model; Bayesian methods.
Ano: 2016 URL: http://archimer.ifremer.fr/doc/00377/48774/49172.pdf
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