fastLink (version 0.6.1)

blockData: blockData

Description

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

Usage

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

Value

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.

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.

Examples

if (FALSE) {
block_out <- blockData(dfA, dfB, varnames = c("city", "birthyear"))
}