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

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Documentation for package ‘skipTrack’ version 0.1.2

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

gibbsStepLi	Gibbs Step Li - One MCMC step for the Li Model
liInference	Perform hyperparameter inference assuming the model given in Li et al. (2022) on a cycle length dataset.
likVec	Monte Carlo estimate of negative marginal log-likelihood of Li model
liMCMC	Runs MCMC algorithm for performing inference using the model from Li et al. (2022)
liSim	Simulate user tracked menstrual cycle data for an individual using the li model.
mixSim	Simulate user tracked menstrual cycle data for an individual using the mixture model.
plot.skipTrack.model	Plot skipTrack.model objects
postBeta	Draw from Posterior Distribution for Beta Parameters
postCij	Sample a vector of values from the full conditional posterior of the c_ij vector
postGamma	Perform a Metropolis-Hastings Step for Drawing a New Gamma
postLambdai	Compute random draw from full conditional posterior for lambda_i in Li algorithm.
postMui	Sample a value from the full conditional posterior of mu_i
postPhi	Metropolis-Hastings step to draw a new value for phi.
postPi	Sample a value from the full conditional posterior of pi
postPii	Compute M-H draw for pi_i in Li algorithm
postRho	Sample a value from the full conditional posterior of rho
postSij	Compute random draw from full conditional posterior for s_ij in Li algorithm.
postTaui	Sample a value from the full conditional posterior of tau_i
print.skipTrack.model	Print skipTrack.model to console
sampleStep	Perform a single step of the MCMC sampling process for skipTrack
skipTrack.diagnostics	skipTrack MCMC Diagnostics
skipTrack.fit	Fits the skipTrack Model using 1 or more MCMC chains
skipTrack.MCMC	Perform one chain of MCMC sampling for the skipTrack model.
skipTrack.results	Get tables of Inference results from skipTrack.fit
skipTrack.simulate	Simulate user-tracked menstrual cycle data for multiple individuals
skipTrack.visualize	Visualize Results from skipTrack.fit
str.skipTrack.model	Report skipTrack.model structure to console
stSim	Simulate user tracked menstrual cycle data for an individual, based on the skipTrack model.
summary.skipTrack.model	Report skipTrack.model results to console