MCMCbaselineEI {MCMCpack} | R Documentation |
MCMCbaselineEI is used to fit Wakefield's baseline ecological inference model for partially observed 2 x 2 contingency tables.
MCMCbaselineEI(r0, r1, c0, c1, burnin=1000, mcmc=50000, thin=10, tune=2.65316, verbose=FALSE, seed=0, alpha0=1, beta0=1, alpha1=1, beta1=1, method="NA", ...)
r0 |
(ntables * 1) vector of row sums from row 0. |
r1 |
(ntables * 1) vector of row sums from row 1. |
c0 |
(ntables * 1) vector of column sums from column 0. |
c1 |
(ntables * 1) vector of column sums from column 1. |
burnin |
The number of burn-in scans for the sampler. |
mcmc |
The number of mcmc scans to be saved. |
thin |
The thinning interval used in the simulation. The number of mcmc iterations must be divisible by this value. |
tune |
Tuning parameter for the Metropolis-Hasting sampling. |
verbose |
A switch which determines whether or not the progress of the sampler is printed to the screen. Information is printed if TRUE. |
seed |
The seed for the random number generator. The code uses the Mersenne Twister, which requires an integer as an input. If nothing is provided, the Scythe default seed is used. |
alpha0 |
alpha parameter for the beta prior on p0. |
beta0 |
beta parameter for the beta prior on p0. |
alpha1 |
alpha parameter for the beta prior on p1. |
beta1 |
beta parameter for the beta prior on p1. |
method |
Parameter determining whether a data augmentation algorithm should be used on the exact posterior (``DA"), or a Metropolis-Hastings algorithm should be used on Wakefield's normal approximation to the posterior (``NA"). For tables with large row and column sums, the preferred method is ``NA." |
... |
further arguments to be passed |
Consider the following partially observed 2 by 2 contingency table:
| Y=0 | | Y=1 | | | |
- - - - - | - - - - - | - - - - - | - - - - - |
X=0 | | Y0 | | | | r0 |
- - - - - | - - - - - | - - - - - | - - - - - |
X=1 | | Y1 | | | | r1 |
- - - - - | - - - - - | - - - - - | - - - - - |
| c0 | | c1 | | N |
where r0, r1, c0, c1, and N are non-negative integers that are observed. The interior cell entries are not observed. It is assumed that Y0|r0 ~ Binomial(r0, p0) and Y1|r1 ~ Binomial(r1,p1). Inference centers on p0 and p1. Wakefield's baseline model starts with the assumption that a priori p0 ~ Beta(alpha0, beta0) and p1 ~ Beta(alpha1, beta1).
An mcmc object that contains the posterior density sample. This object can be summarized by functions provided by the coda package.
Jonathan Wakefield. 2001. ``Ecological Inference for 2 x 2 Tables," Center for Statistics and the Social Sciences Working Paper no. 12. University of Washington.
Andrew D. Martin, Kevin M. Quinn, and Daniel Pemstein. 2003. Scythe Statistical Library 0.4. http://scythe.wustl.edu.
Martyn Plummer, Nicky Best, Kate Cowles, and Karen Vines. 2002. Output Analysis and Diagnostics for MCMC (CODA). http://www-fis.iarc.fr/coda/.
MCMChierEI
, MCMCdynamicEI
,
plot.mcmc
,summary.mcmc
## Not run: posterior <- MCMCbaselineEI(300, 200, 100, 400) plot(posterior) summary(posterior) ## End(Not run)