postMui: Sample a value from the full conditional posterior of mu_i

In skipTrack: A Bayesian Hierarchical Model that Controls for Non-Adherence in Mobile Menstrual Cycle Tracking

Sample a value from the full conditional posterior of mu_i

Description

In our model the data are drawn from LogN(mu_i + log(c_ij), tau_i). The prior for mu_i is given as N(x_i^T %*% beta, rho). This function draws from the conditional posterior of mu_i.

Usage

postMui(yij, cij, taui, xib, rho)

Arguments

yij	Numeric vector, cycle lengths for a single individual
cij	Positive Integer vector, a sampled vector of length(yij) where the corresponding values in cij indicate a sampled number of TRUE cycles in each cycle length given by yij
taui	Numeric > 0, A sampled precision for the yijs
xib	Numeric, result of multiplying x_i^T %*% beta (single value, not vector)
rho	Numeric > 0, sampled prior precision of mu_i

Details

Additionally, note that in order to vectorize the remainder of the MCMC algorithm this function returns the sampled value repeated for length(yij)

Value

Numeric vector, repeated sampled value of length(yij)

skipTrack documentation built on April 3, 2025, 6:21 p.m.