gcimpute: A Package for Missing Data Imputation

gcimpute: A Package for Missing Data Imputation

missing data, single imputation, multiple imputation, Gaussian copula, mixed
data, imputation uncertainty, Python.

This article introduces the Python package gcimpute for missing data imputation.
Package gcimpute can impute missing data with many different variable types, including
continuous, binary, ordinal, count, and truncated values, by modeling data as samples
from a Gaussian copula model. This semiparametric model learns the marginal distribution of each variable to match the empirical distribution, yet describes the interactions
between variables with a joint Gaussian that enables fast inference, imputation with
confidence intervals, and multiple imputation. The package also provides specialized extensions to handle large datasets (with complexity linear in the number of observations)
and streaming datasets (with online imputation). This article describes the underlying
methodology and demonstrates how to use the software package.

Yuxuan Zhao

https://www.jstatsoft.org/article/view/v108i04

Cornell University

February 2024

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