rstan (version 2.9.0-3)

vb-methods: Run Stan's Variational Algorithm for Approximate Posterior Sampling

Description

Approximately draw from a posterior distribution using variational inference. We recommend calling stan or sampling for final inferences and only using vb to get a rough idea of the parameter distributions.

Usage

## S3 method for class 'stanmodel':
vb(object, data = list(), pars = NA, include = TRUE,
    seed = sample.int(.Machine$integer.max, 1),
    init = 'random',
    check_data = TRUE, sample_file = tempfile(fileext = '.csv'),
    algorithm = c("meanfield", "fullrank"), ...)

Arguments

object

An object of class stanmodel.

data

A named list or environment providing the data for the model or a character vector for all the names of objects used as data. See the notes in stan.

pars

If not NA, then a character vector naming parameters, which are included in the output if include = TRUE and excluded if include = FALSE. By default, all parameters are included.

include

Logical scalar indicating whether to include (the default) or exclude the parameters named in pars

seed

The seed for random number generation. The default is generated from 1 to the maximum integer supported by Ron the machine. When a seed is specified by a number, as.integer will be applied to it. If as.integer produc

init

One of digit 0, string "0" or "random", a function that returns a list, or a named list of initial parameter values. "0": initialize all to be zero on the unconstrained support; "

check_data

Logical: if TRUE, the data would be preprocessed; otherwise not. If the data is not checked and preprocessed, it is safe to leave it to be the default TRUE. See the notes in stan

sample_file

A character string of file name for specifying where to write samples for all parameters and other saved quantities. This defaults to a temporary file.

algorithm

One of "meanfield" and "fullrank" indicating which variational inference algorithm is used. meanfield: mean-field approximation; fullrank: full-rank covariance. The default is 'meanfield'.

...

Other optional parameters, refer to the manuals for both CmdStan and Stan.

1. iter(positiveinteger), the maximum number of iterations, defaults to 10000.
2. grad_samples(positiveinteger

Value

• An object of stanfit-class

See Also

stanmodel The manuals of CmdStan and Stan.

Examples

m <- stan_model(model_code = 'parameters {real y;} model {y ~ normal(0,1);}')
f <- vb(m)