R Package MissMech: Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random. To test whether the missing data mechanism, in a set of incompletely observed data, is one of missing completely at random (MCAR). For detailed description see Jamshidian, M. Jalal, S., and Jansen, C. (2014). ”MissMech: An R Package for Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random (MCAR),” Journal of Statistical Software, 56(6), 1-31. URL http://www.jstatsoft.org/v56/i06/.
Keywords for this software
References in zbMATH (referenced in 5 articles , 1 standard article )
Showing results 1 to 5 of 5.
- Frahm, Gabriel; Nordhausen, Klaus; Oja, Hannu: M-estimation with incomplete and dependent multivariate data (2020)
- Izhar Asael Alonzo Matamoros, Alicia Nieto-Reyes: An R package for Normality in Stationary Processes (2020) arXiv
- Imbert, Alyssa; Vialaneix, Nathalie: Exploring, handling, imputing and evaluating missing data in statistical analyses: a review of existing approaches (2018)
- Yuan, Ke-Hai; Jamshidian, Mortaza; Kano, Yutaka: Missing data mechanisms and homogeneity of means and variances-covariances (2018)
- Mortaza Jamshidian; Siavash Jalal; Camden Jansen: MissMech: An R Package for Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random (MCAR) (2014) not zbMATH