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- W2495007373 abstract "When Gaussian copula with linear correlation coefficient is used to model correlated random variables, one crucial issue is to determine a suitable correlation coefficient $rho_z$ in normal space for two variables with correlation coefficient $rho_x$. This paper attempts to address this problem. For two continuous variables, the marginal transformation is approximated by a weighted sum of Hermite polynomials, then, with Mehler's formula, a polynomial of $rho_z$ is derived to approximate the function relationship between $rho_x$ and $rho_z$. If a discrete variable is involved, the marginal transformation is decomposed into piecewise continuous ones, and $rho_x$ is expressed as a polynomial of $rho_z$ by Taylor expansion. For a given $rho_x$, $rho_z$ can be efficiently determined by solving a polynomial equation." @default.
- W2495007373 created "2016-08-23" @default.
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- W2495007373 date "2016-08-02" @default.
- W2495007373 modified "2023-10-16" @default.
- W2495007373 title "Calculating correlation coefficient for Gaussian copula" @default.
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- W2495007373 doi "https://doi.org/10.48550/arxiv.1608.00738" @default.
- W2495007373 hasPublicationYear "2016" @default.
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