# a <- a1 * f1 + a2 * f2 + a3 * f3
# b <- b1 * f1 + b2 * f2 + b3 * f3
# 1 <- f1 + f2 + f3

#Install#
install.packages('R2jags')
install.packages('rjags')
install.packages('coda')
install.packages('ggplot2')
install.packages('simmr')
library(coda)
library(coda)
library(rjags)
library(R2jags)
library(ggplot2)
library(simmr)

#Input data#
  a <- rnorm(1, mean = -29, sd = .2)
  b <- rnorm(1, mean = .56, sd = .02)
  mix = matrix(c(a,b), ncol=2, nrow=1)
  colnames(mix) = c('d13C','d14')

#Source endmembers#
  s_names = c("biomass", "liquid", "coal")
  s_means = matrix(c(-35,-25.5,-23.4,1.10,0,0), ncol=2, nrow=3)
  s_sds = matrix(c(1.8,1.3,1.3,0.05,0,0), ncol=2, nrow=3)  

   simmr_in = simmr_load(mixtures=mix,
                        source_names=s_names,
                        source_means=s_means,
                        source_sds=s_sds)
  

  plot(simmr_in)
  

  plot(simmr_in,xlab=expression(paste(delta^13, "C (\u2030)",sep="")),
       ylab=expression(paste(delta^14, "C (\u2030)",sep="")),
       title='Isospace plot of example data')
  

  simmr_out = simmr_mcmc(simmr_in)
  

  summary(simmr_out,type='diagnostics')

  posterior_predictive(simmr_out)
  

  prior_viz(simmr_out)
  summary(simmr_out,type='statistics')
  plot(simmr_out,type='density')
  plot(simmr_out,type='matrix')
  compare_sources(simmr_out,source_names=c('biomass','coal'))
  compare_sources(simmr_out,source_names=c('biomass','liquid','coal'))