trait ContinuousDistr[T] extends Density[T] with Rand[T]
Represents a continuous Distribution. Why T? just in case.
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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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- def apply(x: T): Double
Returns the unnormalized value of the measure
Returns the unnormalized value of the measure
- Definition Classes
- ContinuousDistr → Density
- final def asInstanceOf[T0]: T0
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- def clone(): AnyRef
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- protected[lang]
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- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @IntrinsicCandidate()
- def condition(p: (T) => Boolean): Rand[T]
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- Rand
- def drawOpt(): Option[T]
Overridden by filter/map/flatmap for monadic invocations.
Overridden by filter/map/flatmap for monadic invocations. Basically, rejeciton samplers will return None here
- Definition Classes
- Rand
- final def eq(arg0: AnyRef): Boolean
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- def equals(arg0: AnyRef): Boolean
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- def filter(p: (T) => Boolean): Rand[T]
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- Rand
- def flatMap[E](f: (T) => Rand[E]): Rand[E]
Converts a random sampler of one type to a random sampler of another type.
Converts a random sampler of one type to a random sampler of another type. Examples: randInt(10).flatMap(x => randInt(3 * x.asInstanceOf[Int]) gives a Rand[Int] in the range [0,30] Equivalently, for(x <- randInt(10); y <- randInt(30 *x)) yield y
- f
the transform to apply to the sampled value.
- Definition Classes
- Rand
- def foreach(f: (T) => Unit): Unit
Samples one element and qpplies the provided function to it.
Samples one element and qpplies the provided function to it. Despite the name, the function is applied once. Sample usage:
for(x <- Rand.uniform) { println(x) }- f
the function to be applied
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- Rand
- def get(): T
- Definition Classes
- Rand
- final def getClass(): Class[_ <: AnyRef]
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- def hashCode(): Int
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- final def isInstanceOf[T0]: Boolean
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- def logApply(x: T): Double
Returns the log unnormalized value of the measure
Returns the log unnormalized value of the measure
- Definition Classes
- ContinuousDistr → Density
- def logPdf(x: T): Double
- def map[E](f: (T) => E): Rand[E]
Converts a random sampler of one type to a random sampler of another type.
Converts a random sampler of one type to a random sampler of another type. Examples: uniform.map(_*2) gives a Rand[Double] in the range [0,2] Equivalently, for(x <- uniform) yield 2*x
- f
the transform to apply to the sampled value.
- Definition Classes
- Rand
- final def ne(arg0: AnyRef): Boolean
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- lazy val normalizer: Double
- final def notify(): Unit
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- final def notifyAll(): Unit
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- def pdf(x: T): Double
Returns the probability density function at that point.
- def sample(n: Int): IndexedSeq[T]
Gets n samples from the distribution.
Gets n samples from the distribution.
- Definition Classes
- Rand
- def sample(): T
Gets one sample from the distribution.
Gets one sample from the distribution. Equivalent to get()
- Definition Classes
- Rand
- def samples: Iterator[T]
An infinitely long iterator that samples repeatedly from the Rand
An infinitely long iterator that samples repeatedly from the Rand
- returns
an iterator that repeatedly samples
- Definition Classes
- Rand
- def samplesVector[U >: T](size: Int)(implicit m: ClassTag[U]): DenseVector[U]
Return a vector of samples.
Return a vector of samples.
- Definition Classes
- Rand
- final def synchronized[T0](arg0: => T0): T0
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- def toString(): String
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- def unnormalizedPdf(x: T): Double
Returns the probability density function up to a constant at that point.
- 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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- @throws(classOf[java.lang.InterruptedException])
- def withFilter(p: (T) => Boolean): Rand[T]
- Definition Classes
- Rand