case class NHPoissonProcess(lambda: VectorD, dt: Double = 1.0, stream: Int = 0) extends TimeVariate with Product with Serializable
This class generates arrival times according to a NHPoissonProcess, an
Non-Homogeneous Process Process (NHPP), where the arrival rate function
'lambda(t)' is piece-wise constant. Rates are constant over basic time
intervals of length 'dt'.
- lambda
the vector of arrival rates
- dt
the length the basic time intervals
- stream
the random number stream
- See also
http://en.wikipedia.org/wiki/Poisson_process#Non-homogeneous
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val
MAXFAC: Int
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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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def
count(a: Double, b: Double): Int
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- TimeVariate
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def
count(tt: Double): Int
Compute the mean as a function of time.
Compute the mean as a function of time.
- tt
the time point for computing the mean
- Definition Classes
- TimeVariate
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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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- Variate
- val dt: Double
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final
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eq(arg0: AnyRef): Boolean
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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
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def
gen: Double
Compute inter-arrival times of the NHPP.
Compute inter-arrival times of the NHPP. 'tlast' is a global variable.
- Definition Classes
- NHPoissonProcess → Variate
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def
gen1(z: Double): Double
Determine the next random number for the particular distribution.
Determine the next random number for the particular distribution. This version allows one paramater.
- z
the limit paramater
- Definition Classes
- NHPoissonProcess → Variate
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def
genTime: Double
Compute arrival times of the NHPP.
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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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def
igen1(z: Double): 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. This version allows one parameter.
- z
the limit parameter
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final
def
isInstanceOf[T0]: Boolean
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- val lambda: VectorD
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val
mean: Double
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- TimeVariate → Variate
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def
meanF(tt: Double): Double
Compute the mean as a function of time.
Compute the mean as a function of time.
- tt
the time point for computing the mean
- Definition Classes
- NHPoissonProcess → TimeVariate
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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def
notifyAll(): Unit
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def
pf(k: Int, a: Double, b: Double): Double
Compute the probability P[ (N(b) - N(a)) = k ].
Compute the probability P[ (N(b) - N(a)) = k ].
- k
the number of arrivals in interval [a,b]
- a
the left end of the interval
- b
the right end of the interval
- Definition Classes
- NHPoissonProcess → TimeVariate
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def
pf(k: Int, tt: Double): Double
Compute the probability of k arrivals occurring in the time interval '[0, tt]'.
Compute the probability of k arrivals occurring in the time interval '[0, tt]'.
- k
the number of arrivals in the time interval
- tt
the upper bound time value
- Definition Classes
- NHPoissonProcess → TimeVariate
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def
pf(k: Int): Double
Compute the probability of k arrivals occurring in the time interval [0, t] where t is the current time.
Compute the probability of k arrivals occurring in the time interval [0, t] where t is the current time.
- k
the number of arrivals in the time interval
- Definition Classes
- NHPoissonProcess → TimeVariate
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def
pf(z: Double): Double
Compute the probability function (pf): The probability density function (pdf) for continuous RV's or the probability mass function (pmf) for discrete RV's.
Compute the probability function (pf): The probability density function (pdf) for continuous RV's or the probability mass function (pmf) for discrete RV's.
- z
the mass point whose probability is sought
- Definition Classes
- TimeVariate → 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
- Definition Classes
- 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
reset(): Unit
Reset the NHPP by resetting 'e' to zero.
Reset the NHPP by resetting 'e' to zero.
- Definition Classes
- NHPoissonProcess → TimeVariate
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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
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def
sgen1(z: Double): 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. This version allows one parameter.
- z
the limit parameter
- Definition Classes
- Variate
- val stream: Int
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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