dvine6dsim: Simulation from a six-variate 1-truncated D-vine copula

In CopulaREMADA: Copula Mixed Models for Multivariate Meta-Analysis of Diagnostic Test Accuracy Studies

Simulation from a six-variate 1-truncated D-vine copula

Description

Simulation from a six-variate 1-truncated D-vine copula.

Usage

dvine6dsim(nsim,tau,qcond,tau2par)

Arguments

nsim	sample size
tau	Kendall's tau values
qcond	function for the inverse conditional copula cdf
tau2par	function for maping Kendall's taus to copula parameters

Details

Choices are 'cop' in rcop are bvn, frk, cln, cln90 (rotated by 90 degrees cln), cln180 (rotated by 180 degrees cln), cln270 (rotated by 270 degrees cln).

See help page for qcondcop for the abbreviations of the copula names.

Value

Nx6 matrix with values in (0,1)

References

Joe H (2011) Dependence comparisons of vine copulae with four or more variables. In: Kurowicka D, Joe H, editors. Dependence Modeling: Handbook on Vine Copulae. Singapore: World Scientific; 2011. p. 139–164

Joe H (2014) Dependence Modeling with Copulas. Chapman & Hall/CRC.

Joe H (2014) CopulaModel: Dependence Modeling with Copulas. Software for book: Dependence Modeling with Copulas, Chapman & Hall/CRC, 2014.

Nikoloulopoulos, A.K. (2024) Joint meta-analysis of two diagnostic tests accounting for within and between studies dependence. Statistical Methods in Medical Research. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/09622802241269645")}

See Also

qcondcop rcop

CopulaREMADA documentation built on Oct. 18, 2024, 1:08 a.m.