| predict.ecoNP {eco} | R Documentation |
Obtains out-of-sample posterior predictions under the fitted
nonparametric Bayesian model for ecological
inference. predict method for class ecoNP and ecoNPX.
## S3 method for class 'ecoNP':
predict(object, newdraw = NULL, subset = NULL, obs = NULL,
verbose = FALSE, ...)
## S3 method for class 'ecoNPX':
predict(object, newdraw = NULL, subset = NULL, obs = NULL,
cond = FALSE, verbose = FALSE, ...)
object |
An output object from 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.
|
obs |
An integer or vector of integers specifying the observation
number(s) whose posterior draws will be used for predictions. The
default is NULL where all the observations in the data set
are selected.
|
cond |
logical. If TRUE, then the conditional prediction
will made for the parametric model with contextual effects. The
default is FALSE.
|
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, http://imai.princeton.edu; Ying Lu, Department of Sociology, University of Colorado at Boulder, ying.lu@Colorado.Edu
eco, ecoNP, summary.eco,
summary.ecoNP