MVN

R package MVN: Multivariate Normality Tests. Performs multivariate normality tests and graphical approaches and implements multivariate outlier detection and univariate normality of marginal distributions through plots and tests.

Keywords for this software

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References in zbMATH (referenced in 24 articles )

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  1. Papadopoulos, Alecos: Accounting for endogeneity in regression models using copulas: a step-by-step guide for empirical studies (2022)
  2. Punzo, Antonio; Bagnato, Luca: Dimension-wise scaled normal mixtures with application to finance and biometry (2022)
  3. Bagnato, Luca; Punzo, Antonio: Unconstrained representation of orthogonal matrices with application to common principal components (2021)
  4. Hallin, Marc; Mordant, Gilles; Segers, Johan: Multivariate goodness-of-fit tests based on Wasserstein distance (2021)
  5. Kostelić, Katarina: Game awareness: a questionnaire (2021)
  6. Rashki, Mohsen: The soft Monte Carlo method (2021)
  7. Ye, Yunfei; Han, Dong: An optimal control chart for finite matrix sequences at some unknown change point (2021)
  8. Al-Thani, Hessa; Lee, Jon: An R package for generating covariance matrices for maximum-entropy sampling from precipitation chemistry data (2020)
  9. Buckby, Jodie; Wang, Ting; Zhuang, Jiancang; Obara, Kazushige: Model checking for hidden Markov models (2020)
  10. Henze, Norbert; Visagie, Jaco: Testing for normality in any dimension based on a partial differential equation involving the moment generating function (2020)
  11. Hessa Al-Thani, Jon Lee: An R Package for generating covariance matrices for maximum-entropy sampling from precipitation chemistry data (2020) arXiv
  12. Chaturvedi, Ajit; Bapat, Sudeep R.; Joshi, Neeraj: A (k)-stage procedure for estimating the mean vector of a multivariate normal population (2019)
  13. Chen, Cathy W. S.; Than-Thi, Hong; So, Mike K. P.: On hysteretic vector autoregressive model with applications (2019)
  14. Cinzia Franceschini, Nicola Loperfido: MaxSkew and MultiSkew: Two R Packages for Detecting, Measuring and Removing Multivariate Skewness (2019) arXiv
  15. Najarzadeh, Dariush: Testing equality of standardized generalized variances of (k) multivariate normal populations with arbitrary dimensions (2019)
  16. Park, Seongoh; Lim, Johan; Wang, Xinlei; Lee, Sanghan: Permutation based testing on covariance separability (2019)
  17. Talebi, Hassan; Mueller, Ute; Tolosana-Delgado, Raimon; van den Boogaart, K. Gerald: Geostatistical simulation of geochemical compositions in the presence of multiple geological units: application to mineral resource evaluation (2019)
  18. Duarte Silva, A. Pedro; Filzmoser, Peter; Brito, Paula: Outlier detection in interval data (2018)
  19. Gómez, José G.: Dependent Lindeberg central limit theorem for the fidis of empirical processes of cluster functionals (2018)
  20. González-Estrada, E.; Villaseñor, J. A.: An R package for testing goodness of fit: goft (2018)

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