Stores the estimated posterior distributions of
the latent abundance or occurrence variables.

## Objects from the Class

Objects can be created by calls of the form `ranef`

.

## Slots

`post`

:An `array`

with nSites rows and Nmax
(K+1) columns and nPrimaryPeriod slices

## Methods

- bup
`signature(object = "unmarkedRanef")`

: Extract the
Best Unbiased Predictors (BUPs) of the latent variables (abundance
or occurrence state). Either the posterior mean or median can be
requested using the `stat`

argument.

- confint
`signature(object = "unmarkedRanef")`

: Compute
confidence intervals.

- plot
`signature(x = "unmarkedRanef", y = "missing")`

:
Plot the posteriors using `xyplot`

- show
`signature(object = "unmarkedRanef")`

: Display the
modes and confidence intervals

## Warnings

Empirical Bayes methods can underestimate the variance of the
posterior distribution because they do not account for uncertainty in
the hyperparameters (lambda or psi). Simulation studies
indicate that the posterior mode can exhibit (3-5
percent) negatively bias as a point
estimator of site-specific abundance. It appears to be safer to use
the posterior mean even though this will not be an integer in general.

## References

Laird, N.M. and T.A. Louis. 1987. Empirical Bayes confidence intervals
based on bootstrap samples. Journal of the American Statistical
Association 82:739--750.

Carlin, B.P and T.A Louis. 1996. Bayes and Empirical Bayes Methods for
Data Analysis. Chapman and Hall/CRC.

Royle, J.A and R.M. Dorazio. 2008. Hierarchical Modeling and Inference
in Ecology. Academic Press.

## See also

## Examples

showClass("unmarkedRanef")

#> Class "unmarkedRanef" [package "unmarked"]
#>
#> Slots:
#>
#> Name: post
#> Class: array