![]() ![]() The following chart shows the data resulting from the above R code. Where $Z$ is a $k$-dimensional vector of independent standard normal random variables, $\mu$ is a $d$-dimensional vector of constants, and $A$ is a $d\times k$ matrix of constants. I'll start by providing the required definition and properties of the multivariate normal distribution, followed by the Gaussian copula, and then I'll provide the algorithm to simulate from the Gauss copula.Ī random vector $X = (X_1, \ldots, X_d)'$ has a multivariate normal distribution if There is a very simple method to simulate from the Gaussian copula which is based on the definitions of the multivariate normal distribution and the Gauss copula. theory (DFT) calculations using the B3LYP 6-31G (d, p) basis set in Gaussian 09W. ![]()
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