A FORTRAN program for generation of multivariate normally distributed random variables

Amitava Ghosh; Pinnaduwa H.S.W. Kulatilake

doi:10.1016/0098-3004(87)90043-4

A FORTRAN program for generation of multivariate normally distributed random variables

Amitava Ghosh, Pinnaduwa H.S.W. Kulatilake

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

The computer program given in this paper generates a set of values for each of the random variables which are distributed according to a multivariate normal distribution. It is written in FORTRAN 77 and is designed to run on a CYBER 175 computer. In generating a set of values, the program either can use actual data of the variables as input to estimate parameter values of the multivariate normal distribution or the parameter values of the multivariate normal distribution can be used directly as input to the program. The theory and the necessary algorithms for the generation are given in detail. Use of the program is illustrated through an example in soil engineering. Monte-Carlo simulation method is used for working out the example.

Original language	English (US)
Pages (from-to)	221-233
Number of pages	13
Journal	Computers and Geosciences
Volume	13
Issue number	3
DOIs	https://doi.org/10.1016/0098-3004(87)90043-4
State	Published - 1987
Externally published	Yes

Keywords

Monte-Carlo simulation
Multivariate normal distribution
Rock engineering
Soil engineering

ASJC Scopus subject areas

Information Systems
Computers in Earth Sciences

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10.1016/0098-3004(87)90043-4

Cite this

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abstract = "The computer program given in this paper generates a set of values for each of the random variables which are distributed according to a multivariate normal distribution. It is written in FORTRAN 77 and is designed to run on a CYBER 175 computer. In generating a set of values, the program either can use actual data of the variables as input to estimate parameter values of the multivariate normal distribution or the parameter values of the multivariate normal distribution can be used directly as input to the program. The theory and the necessary algorithms for the generation are given in detail. Use of the program is illustrated through an example in soil engineering. Monte-Carlo simulation method is used for working out the example.",

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AU - Ghosh, Amitava

AU - Kulatilake, Pinnaduwa H.S.W.

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Y1 - 1987

N2 - The computer program given in this paper generates a set of values for each of the random variables which are distributed according to a multivariate normal distribution. It is written in FORTRAN 77 and is designed to run on a CYBER 175 computer. In generating a set of values, the program either can use actual data of the variables as input to estimate parameter values of the multivariate normal distribution or the parameter values of the multivariate normal distribution can be used directly as input to the program. The theory and the necessary algorithms for the generation are given in detail. Use of the program is illustrated through an example in soil engineering. Monte-Carlo simulation method is used for working out the example.

AB - The computer program given in this paper generates a set of values for each of the random variables which are distributed according to a multivariate normal distribution. It is written in FORTRAN 77 and is designed to run on a CYBER 175 computer. In generating a set of values, the program either can use actual data of the variables as input to estimate parameter values of the multivariate normal distribution or the parameter values of the multivariate normal distribution can be used directly as input to the program. The theory and the necessary algorithms for the generation are given in detail. Use of the program is illustrated through an example in soil engineering. Monte-Carlo simulation method is used for working out the example.

KW - Monte-Carlo simulation

KW - Multivariate normal distribution

KW - Rock engineering

KW - Soil engineering

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A FORTRAN program for generation of multivariate normally distributed random variables

Abstract

Keywords

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