model_bh_variance_intra: Run Hierarchical Bayesian variance-intra model
In priviere/PPBstats: An R package to perform analysis found within PPB programmes

Description Usage Arguments Details Value Author(s) See Also

View source: R/model_bh_variance_intra.R

model_bh_variance_intra runs Hierarchical Bayesian variance-intra model to get intra-population variance on each environment of the network. See details for more information.

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model_bh_variance_intra(data, variable, nb_iterations = 1e+05,
  thin = 10, return.mu = TRUE, return.sigma = TRUE,
  return.epsilon = FALSE, return.DIC = FALSE)

`data`	The data frame on which the model is run. It should come from `format_data_PPBstats.data_agro`
`variable`	The variable on which runs the model
`nb_iterations`	Number of iterations of the MCMC
`thin`	thinning interval to reduce autocorrelations between samples of the MCMC
`return.mu`	Return the value for each entry in each environment and each plot (mu_ijk)
`return.sigma`	Return the value for each intra-population variance in each environment (sigma_ij)
`return.epsilon`	Return the value of all residuals in each environment on each plot (epsilon_ijk)
`return.DIC`	Return the DIC value of the model. See details for more information.

Model on intra-population variance estimates entry effects (mu_ijk) and within-population variance (sigma_ij) on each environment. An environment is a combinaison of a location and a year.

The variance are taken in an inverse Gamma distribution of parameters 10^-6.

More information can be found in the book : https://priviere.github.io/PPBstats_book/family-4.html#variance-intra

For DIC value, see ?dic.samples from the rjags package for more information.

The function returns a list with