Rn_tDensity-class | R Documentation |
\frac{\Gamma\left[(\nu+n)/2\right]}{\Gamma(\nu/2)\nu^{n/2}\pi^{n/2}\left|{\Sigma}\right|^{1/2}}\left[1+\frac{1}{\nu}({\vec{x}}-{\vec{\delta}})^{T}{\Sigma}^{-1}({\vec{x}}-{\vec{\delta}})\right]^{-(\nu+n)/2}
on R^n
Implementation of the function
f \colon R^n \to (0,\infty),\, \vec{x} \mapsto f(\vec{x}) = \frac{\Gamma\left[(\nu+n)/2\right]}{\Gamma(\nu/2)\nu^{n/2}\pi^{n/2}\left|{\Sigma}\right|^{1/2}}\left[1+\frac{1}{\nu}({\vec{x}}-{\vec{\delta}})^{T}{\Sigma}^{-1}({\vec{x}}-{\vec{\delta}})\right]^{-(\nu+n)/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 four parameters representing the dimension n
, the location vector \vec{\delta}
, the variance-covariance matrix \Sigma
which needs to be symmetric positive definite and the degrees of freedom parameter \nu
.
dim
An integer that captures the dimension
delta
A vector of size dim with real entries.
sigma
A matrix of size dim x dim that is symmetric positive definite.
df
A positive numerical value representing the degrees of freedom.
Klaus Herrmann
n <- as.integer(3)
f <- new("Rn_tDensity",dim=n,delta=rep(0,n),sigma=diag(n),df=3)
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