public interface MultivariateProbabilityDistribution
Modifier and Type | Method and Description |
---|---|
double |
cdf(Vector x)
Gets the cumulative probability F(x) = Pr(X ≤ x).
|
Matrix |
covariance()
Gets the covariance matrix of this distribution.
|
double |
density(Vector x)
The density function, which, if exists, is the derivative of F.
|
double |
entropy()
Gets the entropy of this distribution.
|
Vector |
mean()
Gets the mean of this distribution.
|
Vector |
mode()
Gets the mode of this distribution.
|
double |
moment(Vector t)
The moment generating function is the expected value of etX.
|
double cdf(Vector x)
x
- xdouble density(Vector x)
f(x) = dF(X) / dxThis may not always exist. For the discrete cases, this is the probability mass function. It gives the probability that a discrete random variable is exactly equal to some value.
x
- xVector mean()
Vector mode()
Matrix covariance()
double entropy()
double moment(Vector t)
E(etX)This may not always exist.
t
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