predict.eco {eco} | R Documentation |
Obtains out-of-sample posterior predictions under the fitted
parametric and nonparametric Bayesian models for ecological
inference. predict
method for class eco
.
## S3 method for class 'eco': predict(object, newdraw = NULL, subset = NULL, verbose = FALSE, ...)
object |
An output object from eco or ecoNP . |
newdraw |
An optional list containing two matrices (or three
dimensional arrays for the nonparametric model) of MCMC draws
of μ and Σ. Those elements should be named as
mu and Sigma , respectively. The default is the
original MCMC draws stored in object .
|
subset |
A scalar or numerical vector specifying the row
number(s) of mu and Sigma in the output object from
eco . If specified, the posterior draws of parameters for
those rows are used for posterior prediction. The default is
NULL where all the posterior draws are used.
|
verbose |
logical. If TRUE , helpful messages along with a
progress report on the Monte Carlo sampling from the posterior
predictive distributions are printed on the screen. The default is
FALSE .
|
... |
further arguments passed to or from other methods. |
The posterior predictive values are computed using the
Monte Carlo sample stored in the eco
or ecoNP
output
(or other sample if
newdraw
is specified). Given each Monte Carlo sample of the
parameters, we sample the vector-valued latent variable from the
appropriate multivariate Normal distribution. Then, we apply the
inverse logit transformation to obtain the predictive values of
proportions, W. The computation may be slow (especially for the
nonparametric model) if a large Monte Carlo sample of the model
parameters is used. In either case, setting verbose = TRUE
may
be helpful in monitoring the progress of the code.
predict.eco
yields a matrix of class predict.eco
containing the Monte Carlo sample from the posterior predictive
distribution of inner cells of ecological
tables. summary.predict.eco
will summarize the output, and
print.summary.predict.eco
will print the summary.
Kosuke Imai, Department of Politics, Princeton University kimai@Princeton.Edu; Ying Lu, Institute for Quantitative Social Sciences, Harvard University ylu@Latte.Harvard.Edu
eco
, ecoNP
, summary.eco
,
summary.ecoNP