emlinklog function

emlinklog

Expectation-Maximization algorithm for Record Linkage allowing for dependencies across linkage fields

emlinklog(patterns, nobs.a, nobs.b, p.m, p.gamma.j.m, p.gamma.j.u,
iter.max, tol, varnames)

Arguments

• patterns: table that holds the counts for each unique agreement pattern. This object is produced by the function: tableCounts.
• nobs.a: Number of observations in dataset A
• nobs.b: Number of observations in dataset B
• p.m: probability of finding a match. Default is 0.1
• p.gamma.j.m: probability that conditional of being in the matched set we observed a specific agreement pattern.
• p.gamma.j.u: probability that conditional of being in the non-matched set we observed a specific agreement pattern.
• iter.max: Max number of iterations. Default is 5000
• tol: Convergence tolerance. Default is 1e-05
• varnames: The vector of variable names used for matching. Automatically provided if using fastLink() wrapper. Used for clean visualization of EM results in summary functions.

Returns

emlinklog returns a list with the following components: - zeta.j: The posterior match probabilities for each unique pattern.

• p.m: The probability of finding a match.

• p.u: The probability of finding a non-match.

• p.gamma.j.m: The probability of observing a particular agreement pattern conditional on being in the set of matches.

• p.gamma.j.u: The probability of observing a particular agreement pattern conditional on being in the set of non-matches.

• patterns.w: Counts of the agreement patterns observed, along with the Felligi-Sunter Weights.

• iter.converge: The number of iterations it took the EM algorithm to converge.

• nobs.a: The number of observations in dataset A.

• nobs.b: The number of observations in dataset B.

Examples

## Not run:

## Calculate gammas
g1 <- gammaCKpar(dfA$firstname, dfB$firstname)
g2 <- gammaCKpar(dfA$middlename, dfB$middlename)
g3 <- gammaCKpar(dfA$lastname, dfB$lastname)
g4 <- gammaKpar(dfA$birthyear, dfB$birthyear)

## Run tableCounts
tc <- tableCounts(list(g1, g2, g3, g4), nobs.a = nrow(dfA), nobs.b = nrow(dfB))

## Run EM
em.log <- emlinklog(tc, nobs.a = nrow(dfA), nobs.b = nrow(dfB))
## End(Not run)

Author(s)

Ted Enamorado ted.enamorado@gmail.com and Benjamin Fifield