case class RandomVecTrend(dim: Int = 10, trend: FunctionS2S = (x: Double) => 2.0 * x, noise: Variate = Uniform (), stream: Int = 0) extends VariateVec with Product with Serializable
The RandomVecTrend class generates random variate vectors useful for
for creating synthetic time-series data. Applies an additive noise model.
- dim
the dimension/size of the vector (number of elements)
- trend
the function representing deterministic component of the time-series
- noise
the ditribution/variate used to produce the random noise
- stream
the random number stream
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new
RandomVecTrend(dim: Int = 10, trend: FunctionS2S = (x: Double) => 2.0 * x, noise: Variate = Uniform (), stream: Int = 0)
- dim
the dimension/size of the vector (number of elements)
- trend
the function representing deterministic component of the time-series
- noise
the ditribution/variate used to produce the random noise
- 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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- VariateVec
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final
def
asInstanceOf[T0]: T0
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clone(): AnyRef
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- val dim: Int
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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
- RandomVecTrend → VariateVec
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final
def
getClass(): Class[_]
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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
- RandomVecTrend → VariateVec
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final
def
isInstanceOf[T0]: Boolean
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val
mean: VectoD
Compute the vector mean for the particular distribution.
Compute the vector mean for the particular distribution.
- Definition Classes
- RandomVecTrend → VariateVec
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final
def
ne(arg0: AnyRef): Boolean
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- val noise: Variate
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final
def
notify(): Unit
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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
- RandomVecTrend → 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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- val trend: FunctionS2S
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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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def
wait(): Unit
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finalize(): Unit
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