default_hyperpars: Get default values for hyperparameters Prints the list of default values for the hyperparameters

Description

Get default values for hyperparameters Prints the list of default values for the hyperparameters

default_hyperpars(family = "gaussian", link = "identity", nranef = NULL)

family

distribution family of the analysis model (gaussian, binomial, poisson or Gamma)

link

link function (if the link is already given in the family, e.g. family = binomial("logit")) this argument does not need to be specified

nranef

number of random effects

A list containing the default hyperparameters for JointAI models. The elements of the list are

analysis_model: hyperparameters for the analysis model

`mu_reg_main`	mean in the priors for regression coefficients
`tau_reg_main`	precision in the priors for regression coefficients
`a_tau_main`	scale parameter in gamma prior for precision of outcome
`b_tau_main`	rate parameter in gamma prior for precision of outcome

Z: hyperparameters for the random effects in mixed models

`RinvD`	scale matrix in Wishart prior (*) for random effects covariance matrix
`KinvD`	degrees of freedom in Wishart prior for random effects covariance matrix
`a_diag_RinvD`	scale parameter in gamma prior for the diagonal elements of `RinvD`
`b_diag_RinvD`	rate parameter in gamma prior for the diagonal elements of `RinvD`

(*) when there is only one random effect a gamma distribution is used instead of the Wishart

norm: hyperparameters for normal and lognormal imputation models

`mu_reg_norm`	mean in the priors for regression coefficients
`tau_reg_norm`	precision in the priors for regression coefficients
`a_tau_norm`	scale parameter in gamma prior for precision of imputed variable
`b_tau_norm`	rate parameter in gamma prior for precision of imputed variable

logit: hyperparameters for logistic imputation models

`mu_reg_logit`	mean in the priors for regression coefficients
`tau_reg_logit`	precision in the priors for regression coefficients

multinomial: hyperparameters for multinomial imputation models

`mu_reg_multinomial`	mean in the priors for regression coefficients
`tau_reg_multinomial`	precision in the priors for regression coefficients

ordinal: hyperparameters for ordinal imputation models

`mu_reg_ordinal`	mean in the priors for regression coefficients
`tau_reg_ordinal`	precision in the priors for regression coefficients
`mu_delta_ordinal`	mean in the prior for the intercepts
`tau_delta_ordinal`	precision in the priors for the intercepts