generics {geva} | R Documentation

## GEVA Generic Methods

### Description

Exhaustive list of generic methods exported from GEVA. Use `findMethods` to retrieve the specific usages.

### Usage

    inputvalues(object)

    inputweights(object, normalized)

    inputdata(object)

    inputnames(object)

    infolist(object, field, ...)

    infolist(object) <- value

    factors(object)

    factors(object) <- value

    classification.table(object)

    classification.table(object) <- value

    analysis.params(gobject)

    featureTable(object)

    featureTable(object) <- value

    sv(object)

    svattr(S, V)

    elem.class(typedlist)

    elem.class(typedlist) <- value

    groupsets(object)

    groupsets(object) <- value

    groups(object)

    scores(object, group)

    centroids(object)

    offsets(object)

    sv.scores(object)

    qindexes(object)

    qareasizes(object)

    qcount(object)

    quantiles(object)

    quantiles.method(object)

    group.rels(object)

    cluster.method(object)

    results.table(gres)

    sv.data(object)

    variation(object, ...)

    get.summary.method(x)

    get.variation.method(x)

    get.distance.method(x)

    as.SVTable(x, ...)

### Arguments

`object, x, gobject` | Primary object. See the documentation from each class for specific usages
`normalized` | `logical`, whether to return values in the normalized scale
`field` | When used with a information list, returns the information entry with the corresponding name
`...` | Additional parameters. If used with an imported S3 method, passes the arguments to the default `vector`, `matrix` or `data.frame` implementation
`value` | The value to be assigned
`S` | Vector to construct the `S` slot
`V` | Vector to construct the `V` slot
`typedlist` | A `TypedList` object
`group` | Character to filter the returned groups. Omit it to return all groups
`gres` | A `GEVAResults` objec

### Value

See the specific usages for each method.

### Examples

    # Returing analysis parameters from an object
    gsummary <- geva.summarize(geva.ideal.example(),
                               summary.method="mean",
                               variation.method="sd")
    anpars <- analysis.params(gsummary)
    print(anpars)
    # $summary.method
    # [1] "mean"
    # $variation.method
    # [1] "sd"

[Package geva version 1.0.0 Index]