Business Cycle Dating and Plotting Tools
c(person("Majid", "Einian", role = c("aut", "cre"),
email = "m.einian@mbri.ac.ir"))

Bayesian composition estimator: estimating sample (taxonomic) composition from biomarker data
Karel Van den Meersche <k.vdmeersche@nioo.knaw.nl>, Karline Soetaert <k.soetaert@nioo.knaw.nl>
Karel Van den Meersche <k.vdmeersche@nioo.knaw.nl>
Function to estimates taxonomic compositions from biomarker data, using a Bayesian approach.

Bayesian composition estimator: estimating sample (taxonomic)
composition from biomarker data
Karel Van den Meersche <k.vdmeersche@nioo.knaw.nl>, Karline
Soetaert <k.soetaert@nioo.knaw.nl>
Function to estimates taxonomic compositions from
biomarker data, using a Bayesian approach.

Karel Van den Meersche <karel.van_den_meersche@cirad.fr>,
Karline Soetaert <k.soetaert@nioz.nl>
Karel Van den Meersche <karel.van_den_meersche@cirad.fr>

Karel Van den Meersche <karel.van_den_meersche@cirad.fr>, Karline Soetaert <karline.soetaert@nioz.nl>

Bayesian Composition Estimator: Estimating Sample (Taxonomic)
Composition from Biomarker Data
Function to estimate taxonomic compositions from biomarker data, using a Bayesian approach.

Produces an economic evaluation of a Bayesian model in the
form of MCMC simulations. Given suitable variables of cost and
effectiveness / utility for two or more interventions, BCEA
computes the most cost-effective alternative and produces
graphical summaries and probabilistic sensitivity analysis

Produces an economic evaluation of a Bayesian model in the form of MCMC simulations. Given suitable variables of cost and effectiveness / utility for two or more interventions, BCEA computes the most cost-effective alternative and produces graphical summaries and probabilistic sensitivity analysis

MASS, ggplot2, grid, R2jags, R2OpenBUGS, mgcv

Gianluca Baio, Andrea Berardi, Anna Heath
MASS, ggplot2, grid, R2jags, R2OpenBUGS, INLA, mgcv
Produces an economic evaluation of a Bayesian model in the form of MCMC simulations. Given suitable variables of cost and effectiveness / utility for two or more interventions, This package computes the most cost-effective alternative and produces graphical summaries and probabilistic sensitivity analysis.