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Calculation of Multivariate Normal Probabilities by Simulation, with Applications to Maximum Simulated Likelihood Estimation
Open accessAbstract
We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata programs for this purpose: mdraws for deriving draws from the standard uniform density using either Halton or pseudorandom sequences, and an egen function, mvnp(), for calculating the probabilities themselves. Several illustrations show how the programs may be used for maximum simulated likelihood estimation.
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Discrete Choice Methods with Simulation
Train, K. E. (2001) · doi:10.1017/cbo9780511805271 · Cited by 7,784
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Haruna, A., Oumbé, H. T., Kountchou, A. M., & Pilag Kakeu, C. B. (2024) · Borsa Istanbul Review · doi:10.1016/j.bir.2023.11.006 · Cited by 18
Metadata
- Authors
- Cappellari, L., & Jenkins, S. P.
- Venue
- The Stata Journal: Promoting communications on statistics and Stata
- Publisher
- SAGE Publications
- Published
- 2006-06
- Volume
- 6
- Issue
- 2
- Pages
- 156-189
- ISSN
- 1536-867X (ISSN-L)
- 1536-8734
- OpenAlex
- W2142813903
- Cited by
- 193
- References
- 1
- FWCI
- 9.15
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Cappellari, L., & Jenkins, S. P. (2006). Calculation of Multivariate Normal Probabilities by Simulation, with Applications to Maximum Simulated Likelihood Estimation. The Stata Journal: Promoting communications on statistics and Stata. https://doi.org/10.1177/1536867x0600600202
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