case class Normal(mu: Double = 0.0, sigma2: Double = 1.0, stream: Int = 0) extends Variate with Product with Serializable
This class generates Normal (Gaussian) random variates.
This continuous RV models normally distributed data (bell curve).
When summed, most distributions tend to Normal (Central Limit Theorem).
- mu
the mean
- sigma2
the variance (sigma squared)
- stream
the random number stream
- See also
http://www.math.uah.edu/stat/special/Normal.html
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Instance Constructors
- new Normal(mu: Double = 0.0, sigma2: Double = 1.0, stream: Int = 0)
- mu
the mean
- sigma2
the variance (sigma squared)
- stream
the random number stream
Value Members
- final def !=(arg0: Any): Boolean
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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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- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- 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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- final def flaw(method: String, message: String): Unit
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- def gen: Double
Determine the next random number for the particular distribution.
- def gen0: Double
- def gen1(z: Double): Double
Determine the next random number for the particular distribution.
- final def getClass(): Class[_ <: AnyRef]
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- @native() @HotSpotIntrinsicCandidate()
- 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.
- Definition Classes
- Variate
- 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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- Variate
- final def isInstanceOf[T0]: Boolean
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- val mean: Double
Precompute the mean for the particular distribution.
- val mu: Double
- final def ne(arg0: AnyRef): Boolean
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- final def notify(): 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.
- 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
- def productElementNames: Iterator[String]
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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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- protected
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- Variate
- 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
- 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 sigma2: Double
- val stream: Int
- final def synchronized[T0](arg0: => T0): T0
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