R package tmvtnorm: Truncated Multivariate Normal and Student t Distribution. Random number generation for the truncated multivariate normal and Student t distribution. Computes probabilities, quantiles and densities, including one-dimensional and bivariate marginal densities. Computes first and second moments (i.e. mean and covariance matrix) for the double-truncated multinormal case.

References in zbMATH (referenced in 19 articles )

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  1. Levine, Michael; Richards, Donald; Su, Jianxi: Independence properties of the truncated multivariate elliptical distributions (2020)
  2. Bon, Joshua J.; Murray, Kevin; Turlach, Berwin A.: Fitting monotone polynomials in mixed effects models (2019)
  3. Lennon, Hannah; Yuan, Jingsong: Estimation of a digitised Gaussian ARMA model by Monte Carlo expectation maximisation (2019)
  4. Arthur, Joseph; Attarian, Adam; Hamilton, Franz; Tran, Hien: Nonlinear Kalman filtering for censored observations (2018)
  5. Chang, S.-M.; Tzeng, J.-Y.; Chen, R.-B.: Fast Bayesian variable screenings for binary response regressions with small sample size (2017)
  6. Grigorova, Denitsa: EM algorithm for maximum likelihood estimation of correlated probit model for two longitudinal ordinal outcomes (2017)
  7. Theodosiadou, Ourania; Tsaklidis, George: Estimating the positive and negative jumps of asset returns via Kalman filtering. The case of Nasdaq index (2017)
  8. Kim, Hea-Jung; Choi, Taeryon; Jo, Seongil: Bayesian factor analysis with uncertain functional constraints about factor loadings (2016)
  9. Lu, Jiannan; Deng, Alex: Demystifying the bias from selective inference: a revisit to Dawid’s treatment selection problem (2016)
  10. Cui, Shiqi; Guha, Subharup; Ferreira, Marco A. R.; Tegge, Allison N.: HmmSeq: a hidden Markov model for detecting differentially expressed genes from RNA-seq data (2015)
  11. Kim, Hea-Jung: Segmented classification analysis with a class of rectangle-screened elliptical populations (2015)
  12. Kim, Hea-Jung: A best linear threshold classification with scale mixture of skew normal populations (2015)
  13. Mai, The Tien; Alquier, Pierre: A Bayesian approach for noisy matrix completion: optimal rate under general sampling distribution (2015)
  14. Yue, Chen; Chen, Shaojie; Sair, Haris I.; Airan, Raag; Caffo, Brian S.: Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models (2015)
  15. Emery, Xavier; Arroyo, Daisy; Peláez, María: Simulating large Gaussian random vectors subject to inequality constraints by Gibbs sampling (2014)
  16. Grigorova, Denitsa; Encheva, Elitsa; Gueorguieva, Ralitza: EM algorithm for MLE of a probit model for multiple ordinal outcomes (2013)
  17. Zhang, Zhiyong; Wang, Lijuan: Methods for mediation analysis with missing data (2013)
  18. Manjunath, B. G.; Frick, Melanie; Reiss, Rolf-Dieter: Some notes on extremal discriminant analysis (2012)
  19. Griffiths, William: A Gibbs’ sampler for the parameters of a truncated multivariate normal distribution (2004)