| Rn_normalDensity-class | R Documentation |
\frac{1}{\sqrt{(2\pi)^n\det(\Sigma)}}\exp(-((\vec{x}-\vec{\mu})^{T}\Sigma^{-1}(\vec{x}-\vec{\mu}))/2) on R^nImplementation of the function
f \colon R^n \to (0,\infty),\, \vec{x} \mapsto f(\vec{x}) = \frac{1}{\sqrt{(2\pi)^n\det(\Sigma)}}\exp(-((\vec{x}-\vec{\mu})^{T}\Sigma^{-1}(\vec{x}-\vec{\mu}))/2),
where n \in \{1,2,3,\ldots\} is the dimension of the integration domain R^n = \times_{i=1}^n R.
In this case the integral is know to be
\int_{R^n} f(\vec{x}) d\vec{x} = 1.
The instance needs to be created with three parameters representing the dimension n, the location vector \vec{\mu} and the variance-covariance matrix \Sigma which needs to be symmetric positive definite.
dimAn integer that captures the dimension
meanA vector of size dim with real entries.
sigmaA matrix of size dim x dim that is symmetric positive definite.
Klaus Herrmann
n <- as.integer(3)
f <- new("Rn_normalDensity",dim=n,mean=rep(0,n),sigma=diag(n))
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