Title: A Fast Laplace Method for Spatial Generalized Linear Mixed Model
person("Sangwan", "Lee", email = "sangwanlee@yonsei.ac.kr", role = c("cre","aut")),
person("Jaewoo", "Park", email = "jaewoopark88@yonsei.ac.kr", role = "aut"))
Description: Fitting a fast Laplace approximation for Spatial Generalized Linear Mixed Model as
described in Park and Lee (2021) <https://github.com/sangwan93/fastLaplace/blob/main/FastLaplaceMain.pdf>.
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), spelling, mgcv,

Title: Fast Probabilistic Record Linkage with Missing Data
person("Ted", "Enamorado", email = "fastlinkr@gmail.com", role = c("aut", "cre")),
person("Ben", "Fifield", email = "fastlinkr@gmail.com", role = c("aut")),
person("Kosuke", "Imai", email = "kimai@Princeton.edu", role = c("aut"))
Description: Implements a Fellegi-Sunter probabilistic record linkage model that allows for missing data
and the inclusion of auxiliary information. This includes functionalities to conduct a merge of two datasets under the Fellegi-Sunter model
using the Expectation-Maximization algorithm. In addition, tools for preparing, adjusting, and summarizing
data merges are included. The package implements methods described in Enamorado, Fifield,
and Imai (2017) ''Using a Probabilistic Model to Assist Merging of Large-scale Administrative
Imports: Matrix, parallel, foreach, doParallel, gtools, data.table,
stringdist, stringr, Rcpp (>= 0.12.9), Hmisc, FactoClass,
Packaged: 2017-07-09 13:17:11 UTC; benfifield

stringdist, stringr, Rcpp (>= 0.12.9), FactoClass, adagio,
Packaged: 2017-07-11 03:09:00 UTC; benfifield

stringdist, stringr, stringi, Rcpp (>= 0.12.7), FactoClass,
adagio, dplyr, plotrix, grDevices, graphics
Packaged: 2017-09-01 05:38:31 UTC; benfifield

Packaged: 2018-01-26 16:38:36 UTC; benfifield

Packaged: 2018-05-15 19:36:45 UTC; benfifield

Packaged: 2018-11-02 15:23:12 UTC; benfifield

person("Ted", "Enamorado", email = "ted.enamorado@gmail.com", role = c("aut", "cre")),
person("Ben", "Fifield", email = "benfifield@gmail.com", role = c("aut")),
and the inclusion of auxiliary information. This includes functionalities to conduct a merge of two
datasets under the Fellegi-Sunter model using the Expectation-Maximization algorithm. In addition,
tools for preparing, adjusting, and summarizing data merges are included. The package implements methods
described in Enamorado, Fifield, and Imai (2019) ''Using a Probabilistic Model to Assist Merging of
Large-scale Administrative Records'', American Political Science Review and is available
Packaged: 2020-04-25 22:01:06 UTC; benfifield