Bivariate conditioning approximations for multivariate normal probabilities
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Publication:261036
DOI10.1007/s11222-014-9468-yzbMath1332.62055OpenAlexW2067583625MaRDI QIDQ261036
Publication date: 22 March 2016
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11222-014-9468-y
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Uses Software
Cites Work
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- Some results on the truncated multivariate \(t\) distribution
- Computation of multivariate normal and \(t\) probabilities
- The Estimation of Multinomial Probit Models: A New Calibration Algorithm
- Algorithm AS 195: Multivariate Normal Probabilities with Error Bound
- Likelihood inference in a correlated probit regression model
- The Efficient Generation of Random Orthogonal Matrices with an Application to Condition Estimators
- Approximations to Multivariate Normal Rectangle Probabilities Based on Conditional Expectations
- Moments of the censored and truncated bivariate normal distribution
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