postCij: Sample a vector of values from the full conditional posterior...

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

Sample a vector of values from the full conditional posterior of the c_ij vector

Description

In our model the data are drawn from LogN(mu_i + log(c_ij), tau_i) The prior for c_ij is a categorical prior with category probabilities pi1, ..., pik, and c_ij can take values 1, ..., k where k is the length of pi. This function samples from the full conditional posterior of all c_ijs, given vectors of equal length yijs, muis, tauis

Usage

postCij(yijs, pi, muis, tauis)

Arguments

yijs	Numeric Vector, cycle lengths
pi	Numeric vector, must sum to 1. Sampled probabilities for c_ijs
muis	Numeric vector, log of sampled mean for all individuals yijs
tauis	Numeric vector > 0, sampled precision for all individuals yijs

Value

Integer vector

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