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chomper

A Comprehensive Hit or Miss Probabilistic Entity Resolution Model

v0.1.3 · Mar 16, 2026 · GPL (>= 3)

Description

Provides Bayesian probabilistic methods for record linkage and entity resolution across multiple datasets using the Comprehensive Hit Or Miss Probabilistic Entity Resolution (CHOMPER) model. The package implements three main inference approaches: (1) Evolutionary Variational Inference for record Linkage (EVIL), (2) Coordinate Ascent Variational Inference (CAVI), and (3) Markov Chain Monte Carlo (MCMC) with split and merge process. The model supports both discrete and continuous fields, and it performs locally-varying hit mechanism for the attributes with multiple truths. It also provides tools for performance evaluation based on either approximated variational factors or posterior samples. The package is designed to support parallel computing with multi-threading support for EVIL to estimate the linkage structure faster.

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installed package size

installed size is  9.8Mb
  sub-directories of 1Mb or more:
    libs   9.1Mb
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installed package size

installed size is 10.4Mb
  sub-directories of 1Mb or more:
    libs   9.6Mb

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NOTE 4 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 16, 2026
NOTE r-oldrel-macos-arm64

installed package size

installed size is  9.8Mb
  sub-directories of 1Mb or more:
    libs   9.1Mb

Dependency Network

Dependencies Reverse dependencies Rcpp chomper

Version History

new 0.1.3 Mar 16, 2026