Some results on the multivariate truncated normal distribution

By W. Horrace. 2005

201 citations recorded by the source corpus.

This note formalizes some analytical results on the n-dimensional multivariate truncated normal distribution where truncation is one-sided and at an arbitrary point. Results on linear transformations, marginal and conditional distributions, and independence are provided. Also, results on log-concavity, A-unimodality and the MTP2 property are derived.

Subfields: Artificial Intelligence, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/8d27e37666553f8151b802cb6c6a4f4261ec2cca

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. P. Schmidt
2. Artem Prokhorov
3. Sujit Kumar Ghosh
4. Christine E. Amsler
5. Yifang Li

In Management Science and Operations Research

1. Christine E. Amsler
2. P. Schmidt
3. Artem Prokhorov
4. Sujit Kumar Ghosh
5. Yifang Li
6. William H. Greene
7. Christopher F. Parmeter
8. Subal C. Kumbhakar

In Statistics and Probability

1. P. Schmidt
2. Artem Prokhorov
3. Sujit Kumar Ghosh
4. Christine E. Amsler
5. Yifang Li

Citations in the corpus

• Using Copulas to Model Time Dependence in Stochastic Frontier Models (2014, background): “In case there is in fact no independence the QMLE standard errors need to be adjusted to account for that (see, e.g., Hayashi, 2000, Section 8.7).”
• Efficient sampling methods for truncated multivariate normal and student-t distributions subject to linear inequality constraints (2015, background): “A good collection of statistical properties of TMVN distributions can be found in Horrace (2005). In this paper, the proposed sampling method requires R̃ to be a m×p matrix with rank m ≤ p.”