Calculation of Multivariate Normal Probabilities by Simulation, with Applications to Maximum Simulated Likelihood Estimation

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10419/18477

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DC Field	Value	Language
dc.creator	Cappellari, Lorenzo	-
dc.creator	Jenkins, Stephen P.	-
dc.date	2006	-
dc.date.accessioned	2013-10-16T07:00:11Z	-
dc.date.available	2013-10-16T07:00:11Z	-
dc.date.issued	2013-10-16	-
dc.identifier	http://hdl.handle.net/10419/18477	-
dc.identifier	ppn:512766576	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/10419/18477	-
dc.description	We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata programs for this purpose: mvdraws for deriving draws from the standard uniform density using either Halton or pseudo-random 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.	-
dc.language	eng	-
dc.publisher	Deutsches Institut für Wirtschaftsforschung (DIW) Berlin	-
dc.relation	DIW-Diskussionspapiere 584	-
dc.rights	http://www.econstor.eu/dspace/Nutzungsbedingungen	-
dc.subject	ddc:330	-
dc.subject	Simulation estimation	-
dc.subject	maximum simulated likelihood	-
dc.subject	multivariate probit	-
dc.subject	Halton sequences	-
dc.subject	pseudo-random sequences	-
dc.subject	multivariate normal	-
dc.title	Calculation of Multivariate Normal Probabilities by Simulation, with Applications to Maximum Simulated Likelihood Estimation	-
dc.type	doc-type:workingPaper	-
Appears in Collections:	EconStor

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