case class _HyperExponential(mu: Double = 1.0, sigma: Double = 2, stream: Int = 0) extends Variate with Product with Serializable
This class generates HyperExponential
random variates.
This continuous RV models the time until an event occurs (higher coefficient
of variation than exponential distribution). FIX
- mu
the mean
- sigma
the standard deviation
- stream
the random number stream
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Instance Constructors
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new
_HyperExponential(mu: Double = 1.0, sigma: Double = 2, stream: Int = 0)
- mu
the mean
- sigma
the standard deviation
- 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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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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def
discrete: Boolean
Determine whether the distribution is discrete or continuous.
Determine whether the distribution is discrete or continuous.
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final
def
eq(arg0: AnyRef): Boolean
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def
finalize(): Unit
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final
def
flaw(method: String, message: String): Unit
Show the flaw by printing the error message.
Show the flaw by printing the error message.
- method
the method where the error occurred
- message
the error message
- Definition Classes
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def
gen: Double
Determine the next random number for the particular distribution.
Determine the next random number for the particular distribution.
- Definition Classes
- _HyperExponential → Variate
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final
def
getClass(): Class[_]
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def
igen: Int
Determine the next random integer for the particular distribution.
Determine the next random integer for the particular distribution. It is only valid for discrete random variates.
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- Variate
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final
def
isInstanceOf[T0]: Boolean
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val
mean: Double
- Definition Classes
- _HyperExponential → Variate
- val mu: Double
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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: Double): Double
Compute the probability function (pf): Either (a) the probability density function (pdf) for continuous RV's or (b) the probability mass function (pmf) for discrete RV's.
Compute the probability function (pf): Either (a) the probability density function (pdf) for continuous RV's or (b) the probability mass function (pmf) for discrete RV's.
- z
the mass point whose probability density/mass is sought
- Definition Classes
- _HyperExponential → Variate
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def
pmf(k: Int = 0): Array[Double]
Return the entire probability mass function (pmf) for finite discrete RV's.
Return the entire probability mass function (pmf) for finite discrete RV's.
- k
number of objects of the first type
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- Variate
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val
r: Random
Random number stream selected by the stream number
Random number stream selected by the stream number
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- Variate
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def
sgen: String
Determine the next random string for the particular distribution.
Determine the next random string for the particular distribution. For better random strings, overide this method.
- Definition Classes
- Variate
- val sigma: Double
- val stream: Int
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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final
def
wait(): Unit
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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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