the Stratified Simple Random Sampling design - BLE_SSRS() - (both without replacement), to the Ratio estimator (using auxiliary
information) - BLE_Ratio() - and to categorical data - BLE_Categorical().
Imports: MASS, Matrix, stats, matrixcalc

Title: Different Models of Posterior Distributions of Adjusted Odds
Description: Generates different posterior distributions of adjusted odds ratio under different priors of sensitivity and specificity, and plots the models for comparison. It also provides estimations for the specifications of the models using diagnostics of exposure status with a non-linear mixed effects model. It implements the methods that are first proposed by Chu et al. (2006) <doi:10.1016/j.annepidem.2006.04.001> and Chu et al. (2010) <doi:10.1177/0272989X09353452>.
Imports: dplyr, ggplot2, rstan (>= 2.16.2), lme4,

Author: Jinhui Yang, Haitao Chu, and Lifeng Lin

Description: Generates different posterior distributions of adjusted odds ratio under different priors of sensitivity and specificity, and plots the models for comparison. It also provides estimations for the specifications of the models using diagnostics of exposure status with a non-linear mixed effects model. It implements the methods that are first proposed in <doi:10.1016/j.annepidem.2006.04.001> and <doi:10.1177/0272989X09353452>.

Imports: methods, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rstan (>=
2.18.1), rstantools (>= 2.1.1), dplyr, ggplot2, lme4

Title: Computation of Bayes factors for interrupted time-series designs
Author: Richard D. Morey, Rivka de Vries
Description: The BayesSingleSub package is a suite of functions for
computing various Bayes factors for interrupted time-series,
based on the models described in de Vries and Morey

Description: The BayesSingleSub package is a suite of functions for computing various Bayes factors for interrupted time-series, based on the models described in de Vries and Morey (2013).

Title: Bayesian Spectral Analysis Techniques
Author: Rosen, O., Wood, S. and Stoffer, D.
Description: An implementation of methods for spectral analysis using the Bayesian framework. It includes functions for modelling spectrum as well as appropriate plotting and output estimates. There is segmentation capability with RJ MCMC (Reversible Jump Markov Chain Monte Carlo). The package takes these methods predominantly from the 2012 paper "AdaptSPEC: Adaptive Spectral Estimation for Nonstationary Time Series" <DOI:10.1080/01621459.2012.716340>.
Packaged: 2017-02-21 23:06:27 UTC; andrewferris