What question did this study set out to answer?

The aim is to develop a nonparametric copula-based method for imputing missing data in multivariate dependent variables.

A nonparametric copula-based imputation method

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Randomized trial demonstrates effective imputation of multivariate missing data, highlighting flexibility and performance.

The aim is to develop a nonparametric copula-based method for imputing missing data in multivariate dependent variables.
Proposed NPCoImp method leverages empirical beta copula for imputing missing values.
Performed Monte Carlo study for evaluating NPCoImp against classical methods and competing algorithms.
Implementation of NPCoImp is available in an R package on CRAN.
NPCoImp maintains complex dependence structure regardless of sample size and missing data proportion.
Showed improved effectiveness compared to classical imputation methods and competitors like CoImp and missForest.
Results validated through empirical case studies in agriculture.

Lascio et al. (2026) studied this question.

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