sbgcop

R package sbgcop: Semiparametric Bayesian Gaussian copula estimation and imputation. This package estimates parameters of a Gaussian copula, treating the univariate marginal distributions as nuisance parameters as described in Hoff(2007). It also provides a semiparametric imputation procedure for missing multivariate data.

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References in zbMATH (referenced in 5 articles )

Showing results 1 to 5 of 5.
Sorted by year (citations)

  1. Yuxuan Zhao, Madeleine Udell: gcimpute: A Package for Missing Data Imputation (2022) arXiv
  2. Cui, Ruifei; Groot, Perry; Heskes, Tom: Learning causal structure from mixed data with missing values using Gaussian copula models (2019)
  3. Härdle, Karl Wolfgang; Okhrin, Ostap; Okhrin, Yarema: Basic elements of computational statistics (2017)
  4. Hoff, Peter D.: Extending the rank likelihood for semiparametric copula estimation (2007)
  5. Jun Yan: Enjoy the Joy of Copulas: With a Package copula (2007) not zbMATH