R: summary methods for '"RLBigData"' objects.

summary.RLBigData {RecordLinkage} | R Documentation

## summary methods for `"RLBigData"` objects.

### Description

Shows summarized information on a `"RLBigDataDedup"` or `"RLBigDataDedup"` object.

### Usage

      ## S3 method for class 'RLBigDataDedup'
    summary(object, ...)
      ## S3 method for class 'RLBigDataLinkage'
    summary(object, ...)
      ## S3 method for class 'summaryRLBigDataDedup'
    print(x, ...)
      ## S3 method for class 'summaryRLBigDataLinkage'
    print(x, ...)

### Arguments

`object` | The object for which to show a summary.
`x` | Return value of the summary function.
`...` | Additional arguments from the generic function are ignored.

### Details

The `summary` methods return a list of the format shown below. The print method displays this information on the console in a user-friendly format.

Blocking fields are displayed in a style like [attr1], [attr2, attr3], where attr1 etc. are column names and attributes within brackets represent one blocking iteration. See `compare.dedup` or `RLBigDataDedup` for an explanation of blocking criteria.

### Value

For `summary`, a list with components

`nData` | Only for the `"RLBigDataDedup"` method: Number of records in the dataset.
`nData1` | Only for the `"RLBigDataLinkage"` method: Number of records in dataset 1.
`nData2` | Only for the `"RLBigDataLinkage"` method: Number of records in dataset 2.
`attributes` | Column names of dataset(s).
`blockFld` | Blocking definition as a list of character vectors, representing column names.
`nPairs` | Number of record pairs
`nMatches` | Number of matches in the set of record pairs.
`nNonMatches` | Number of non-matches in the set of record pairs.
`nUnkonwn` | Number of record pairs with unknown matching status.
`weightHist` | Only if weights have been calculated for `object`: a summary of the weights in histogram style.

### Author(s)

Andreas Borg, Murat Sariyar

### See Also

`summary` `"RLBigData"` `RLBigDataDedup`, `RLBigDataLinkage`

### Examples

      data(RLdata500)
      rpairs <- RLBigDataDedup(RLdata500, identity = identity.RLdata500,
         blockfld=list(1,3,5:7))
      rpairs <- epiWeights(rpairs)
      summary(rpairs)

[Package RecordLinkage version 0.4-11.2 Index]