blockData function

blockData

Contains functionalities for blocking two data sets on one or more variables prior to conducting a merge.

blockData(dfA, dfB, varnames, window.block, window.size,
kmeans.block, nclusters, iter.max, n.cores)

Arguments

• dfA: Dataset A - to be matched to Dataset B
• dfB: Dataset B - to be matched to Dataset A
• varnames: A vector of variable names to use for blocking. Must be present in both dfA and dfB
• window.block: A vector of variable names indicating that the variable should be blocked using windowing blocking. Must be present in varnames.
• window.size: The size of the window for window blocking. Default is 1 (observations +/- 1 on the specified variable will be blocked together).
• kmeans.block: A vector of variable names indicating that the variable should be blocked using k-means blocking. Must be present in varnames.
• nclusters: Number of clusters to create with k-means. Default value is the number of clusters where the average cluster size is 100,000 observations.
• iter.max: Maximum number of iterations for the k-means algorithm to run. Default is 5000
• n.cores: Number of cores to parallelize over. Default is NULL.

Returns

A list with an entry for each block. Each list entry contains two vectors --- one with the indices indicating the block members in dataset A, and another containing the indices indicating the block members in dataset B.

Examples

## Not run:

block_out <- blockData(dfA, dfB, varnames = c("city", "birthyear"))
## End(Not run)