case class NormalVec(mu: VectoD, cov: MatrixD, stream: Int = 0) extends VariateVec with Product with Serializable
The NormalVec class generates Normal (Gaussian) random variate vectors according
to the Multivariate Normal distribution with mean 'mu' and covariance 'cov'.
This continuous RVV models normally distributed multidimensional data.
- mu
the mean vector
- cov
the covariance matrix
- stream
the random number stream
- See also
http://onlinelibrary.wiley.com/doi/10.1111/1467-9639.00037/pdf
http://www.statlect.com/mcdnrm1.htm
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Instance Constructors
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new
NormalVec(mu: VectoD, cov: MatrixD, stream: Int = 0)
- mu
the mean vector
- cov
the covariance matrix
- stream
the random number stream
Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: Any): Boolean
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var
_discrete: Boolean
Indicates whether the distribution is discrete or continuous (default)
Indicates whether the distribution is discrete or continuous (default)
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- protected
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- VariateVec
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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- @throws( ... ) @native() @HotSpotIntrinsicCandidate()
- val cov: MatrixD
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def
discrete: Boolean
Determine whether the distribution is discrete or continuous.
Determine whether the distribution is discrete or continuous.
- Definition Classes
- VariateVec
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final
def
eq(arg0: AnyRef): Boolean
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final
def
flaw(method: String, message: String): Unit
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def
gen: VectoD
Determine the next random double vector for the particular distribution.
Determine the next random double vector for the particular distribution.
- Definition Classes
- NormalVec → VariateVec
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final
def
getClass(): Class[_]
- Definition Classes
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- Annotations
- @native() @HotSpotIntrinsicCandidate()
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def
igen: VectoI
Determine the next random integer vector for the particular distribution.
Determine the next random integer vector for the particular distribution. It is only valid for discrete random variates.
- Definition Classes
- NormalVec → VariateVec
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final
def
isInstanceOf[T0]: Boolean
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def
mean: VectoD
Compute the vector mean for the particular distribution.
Compute the vector mean for the particular distribution.
- Definition Classes
- NormalVec → VariateVec
- val mu: VectoD
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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def
pf(z: VectoD): Double
Compute the probability function (pf): The probability density function (pdf) for continuous RVV's or the probability mass function (pmf) for discrete RVV's.
Compute the probability function (pf): The probability density function (pdf) for continuous RVV's or the probability mass function (pmf) for discrete RVV's.
- z
the mass point/vector whose probability is sought
- Definition Classes
- NormalVec → VariateVec
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val
r: Random
Random number stream selected by the stream number
Random number stream selected by the stream number
- Attributes
- protected
- Definition Classes
- VariateVec
- val stream: Int
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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final
def
wait(): Unit
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def
finalize(): Unit
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