Adds correlation between time-course relative effects

This uses a Wishart prior as default for modelling the correlation

Usage

write.cor(model, fun, omega = NULL, class.effect = list())

model: A character object of JAGS MBNMA model code
fun: An object of class "timefun" generated (see Details) using any of tloglin(), tpoly(), titp(), temax(), tfpoly(), tspline() or tuser()
omega: DEPRECATED IN VERSION 0.2.3 ONWARDS (~uniform(-1,1) now used for correlation between parameters rather than a Wishart prior). A scale matrix for the inverse-Wishart prior for the covariance matrix used to model the correlation between time-course parameters (see Details for time-course functions). omega must be a symmetric positive definite matrix with dimensions equal to the number of time-course parameters modelled using relative effects (pool="rel"). If left as NULL (the default) a diagonal matrix with elements equal to 1 is used.
class.effect: A list of named strings that determines which time-course parameters to model with a class effect and what that effect should be ("common" or "random"). For example: list(emax="common", et50="random").