Package 'blink'

Check whether 2 records which are estimated to be linked have the same IDs

Description

Check whether 2 records which are estimated to be linked have the same IDs

Usage

check_IDs(recpair, identity_vector)

Arguments

recpair	A record pair
identity_vector	A vector of the unique ids

Value

Whether or not two records which are estimated to be linked have the same unique ids

Examples

id <- c(1,2,3,4,5,1,7,8,9,10,11,12,13,14,15,16,17,18,19,20)
rec1 <- 6
rec2 <- 1
check_IDs(recpair=c(rec1,rec2),identity_vector=id)

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identity.RLdata500

Description

Unique identifier for RLdata500 the corresponds to the record number format A vector that contains the codeid

Usage

identity.RLdata500

Format

An object of class numeric of length 500.

---

Function that returns the shared MPMMS (except with an easier condition to code than JASA paper). Function to make a list of vectors of estimated links by "P(MPMMS)>0.5" method Note: The default settings return only MPMMSs with multiple members.

Description

Function that returns the shared MPMMS (except with an easier condition to code than JASA paper). Function to make a list of vectors of estimated links by "P(MPMMS)>0.5" method Note: The default settings return only MPMMSs with multiple members.

Usage

links(lam.gs = lam.gs, include.singles = FALSE, show.as.multiple = FALSE)

Arguments

lam.gs	The estimated linkage structure with a default of 10 iterations
include.singles	Do not include the singleton records
show.as.multiple	Always return MPMMSs that have more than one member

Value

Returns the shared MPMMS

Examples

lam.gs <- matrix(c(1,1,2,2,3,3,5,6,4,3,4,5,3,2,4,1,2,3,4,2),ncol=20,  nrow=4)
links(lam.gs)

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This function takes a set of pairwise links and identifies correct, incorrect, and missing links (correct = estimated and true, incorrect = estimated but not true, missing = true but not estimated)

Description

This function takes a set of pairwise links and identifies correct, incorrect, and missing links (correct = estimated and true, incorrect = estimated but not true, missing = true but not estimated)

Usage

links.compare(est.links.pair, true.links.pair, counts.only = TRUE)

Arguments

est.links.pair	The number of estimated links
true.links.pair	The number of true links
counts.only	State whether or not counts only is true or false

Value

Gives a vector of the estimated and true links, estimated but not true links, and the true but not estimated links

Examples

id <- c(1,2,3,4,5,1,7,8,9,10,11,12,13,14,15,16,17,18,19,20)
lam.gs <- matrix(c(1,1,2,2,3,3,5,6,4,3,4,5,3,2,4,1,2,3,4,2),ncol=20, nrow=4)
est.links <- links(lam.gs)
true.links <- links(matrix(id,nrow=1))
est.links.pair <- pairwise(est.links)
links.compare(est.links.pair, true.links=id)

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Function to compute a record's Maximal Matching Set (MMS) based on a single linkage structure

Description

Function to compute a record's Maximal Matching Set (MMS) based on a single linkage structure

Usage

mms(lambda, record)

Arguments

lambda	The linkage structure
record	A vector of records

Value

Computes a records MMS

Examples

lambda <- matrix(c(1,1,2,2,3,3),ncol=3)
record <- c(1,10,3,5,20,2)
mms(lambda=lambda, record=record)

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Function to compute a record's MPMMS based on a Gibbs sampler. Note: It returns a list of the MPMMS ($mpmms) and its probability ($prob)

Description

Function to compute a record's MPMMS based on a Gibbs sampler. Note: It returns a list of the MPMMS ($mpmms) and its probability ($prob)

Usage

mpmms(lam.gs, record)

Arguments

lam.gs	The gibbs sampler
record	A specific record

Value

Returns a list of the MPMSS and the associated probabilities.

Examples

lam.gs <- matrix(c(1,1,2,2,3,3,5,6,4,3,4,5,3,2,4,1,2,3,4,2),ncol=20,  nrow=4)
record <- c(1,3,1,3,1,3,1,3,1,3,1,3,1,3,1,3,1,3,1,3)
mpmms(lam.gs=lam.gs, record=record)

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Function to take links list that may contain 3-way, 4-way, etc. and reduce it to pairwise only (e.g., a 3-way link 12-45-78 is changed to 2-way links: 12-45, 12-78, 45-78

Description

Function to take links list that may contain 3-way, 4-way, etc. and reduce it to pairwise only (e.g., a 3-way link 12-45-78 is changed to 2-way links: 12-45, 12-78, 45-78

Usage

pairwise(.links)

Arguments

.links

A vector of records that are linked to one another

Value

Returns two ways links of records

Examples

id <- c(1,2,3,4,5,1,7,8,9,10,11,12,13,14,15,16,17,18,19,20)
lam.gs <- matrix(c(1,1,2,2,3,3,5,6,4,3,4,5,3,2,4,1,2,3,4,2),ncol=20, nrow=4)
est.links <- links(lam.gs)
est.links.pair <- pairwise(est.links)

---

Gibbs sampler for empirically motivated Bayesian record linkage

Description

Gibbs sampler for empirically motivated Bayesian record linkage

Usage

rl.gibbs(
  file.num = file.num,
  X.s = X.s,
  X.c = X.c,
  num.gs = num.gs,
  a = a,
  b = b,
  c = c,
  d = d,
  M = M
)

Arguments

file.num	The number of the file
X.s	A vector of string variables
X.c	A vector of categorical variables
num.gs	Total number of gibb iterations
a	Shape parameter of Beta prior
b	Scale parameter of Beta prior
c	Positive constant
d	Any distance metric measuring the latent and observed string
M	The true value of the population size

Value

lambda.out The estimated linkage structure via Gibbs sampling

Examples

data(RLdata500)
X.c <- as.matrix(RLdata500[c("by","bm","bd")])[1:3,]
p.c <- ncol(X.c)
X.s <- as.matrix(RLdata500[c(1,3)])[1:3,]
p.s <- ncol(X.s)
file.num <- rep(c(1,1,1),c(1,1,1))
d <- function(string1,string2){adist(string1,string2)}
lam.gs <- rl.gibbs(file.num,X.s,X.c,num.gs=2,a=.01,b=100,c=1,d, M=3)

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RLdata500

Description

Data on synthetic generation of German names with 500 total records and 10 precent duplication.

Usage

RLdata500

Format

A data frame with five variables: fname_c1,lname_c1, by, codebm, bd.

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