R: Repeatedly estimate model using resampling with replacement

mxComputeBootstrap {OpenMx} | R Documentation

## Repeatedly estimate model using resampling with replacement

### Description

This is a low-level compute plan object to perform resampling with replacement.

### Usage

    mxComputeBootstrap(data, plan, replications=200, ...,
                            verbose=0L, parallel=TRUE, freeSet=NA_character_,
    			OK=c("OK", "OK/green"), only=NA_integer_)

### Arguments

`data` | A vector of dataset or model names.
`plan` | The compute plan used to optimize the model for each data set.
`replications` | The number of resampling replications. If available, replications from prior mxBootstrap invocations will be reused.
`...` | Not used. Forces remaining arguments to be specified by name.
`verbose` | For levels greater than 0, enables runtime diagnostics
`parallel` | Whether to process the replications in parallel
`freeSet` | names of matrices containing free variables
`OK` | The set of status code that are considered successful
`only` | When provided, only the given replication from a prior run of `mxBootstrap` will be performed. See details.

### Details

The ‘only’ option facilitates investigation of a single replication attempt.

### Value

Output is stored in the compute object's `output` slot. Specifically, `model$compute$output$raw` contains a data frame with parameters in columns and replications in rows. In addition to parameters, the `seed`, `fit`, and `statusCode` of the replication is also included.

When ‘only’ is set to a particular replications, the weight vectors (one per dataset) are also returned in the compute object's `output` slot. `model$compute$output$weight` is a character vector (by dataset name) of numeric vectors (the weights). These weights can be used to recreate a model identical to the model used in the given replication.

### See Also

`mxBootstrap`, `as.statusCode`

[Package OpenMx version 2.9.6 Index]