case class Binomial(n: Int, p: Double)(implicit rand: RandBasis) extends DiscreteDistr[Int] with Moments[Double, Double] with Product with Serializable
A binomial distribution returns how many coin flips out of n are heads, where numYes is the probability of any one coin being heads.
- n
is the number of coin flips
- p
the probability of any one being true
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- final def ##: Int
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- def apply(x: Int): Double
Returns the unnormalized value of the measure
Returns the unnormalized value of the measure
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- DiscreteDistr → Density
- final def asInstanceOf[T0]: T0
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- def condition(p: (Int) => Boolean): Rand[Int]
- Definition Classes
- Rand
- def draw(): Int
Gets one sample from the distribution.
- def drawOpt(): Option[Int]
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
- def entropy: Double
with an additive O(1/n) term
- final def eq(arg0: AnyRef): Boolean
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- def filter(p: (Int) => Boolean): Rand[Int]
- Definition Classes
- Rand
- def flatMap[E](f: (Int) => 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: (Int) => 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
- Definition Classes
- Rand
- def get(): Int
- Definition Classes
- Rand
- final def getClass(): Class[_ <: AnyRef]
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- final def isInstanceOf[T0]: Boolean
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- def logApply(x: Int): Double
Returns the log unnormalized value of the measure
Returns the log unnormalized value of the measure
- Definition Classes
- DiscreteDistr → Density
- def logProbabilityOf(k: Int): Double
- Definition Classes
- Binomial → DiscreteDistr
- def map[E](f: (Int) => 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
- def mean: Double
- def mode: Double
- val n: Int
- 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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- val p: Double
- def probabilityOf(k: Int): Double
Returns the probability of that draw.
Returns the probability of that draw.
- Definition Classes
- Binomial → DiscreteDistr
- def productElementNames: Iterator[String]
- Definition Classes
- Product
- def sample(n: Int): IndexedSeq[Int]
Gets n samples from the distribution.
Gets n samples from the distribution.
- Definition Classes
- Rand
- def sample(): Int
Gets one sample from the distribution.
Gets one sample from the distribution. Equivalent to get()
- Definition Classes
- Rand
- def samples: Iterator[Int]
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 >: Int](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
- Definition Classes
- Binomial → AnyRef → Any
- def unnormalizedLogProbabilityOf(x: Int): Double
- Definition Classes
- DiscreteDistr
- def unnormalizedProbabilityOf(x: Int): Double
Returns the probability of that draw up to a constant
Returns the probability of that draw up to a constant
- Definition Classes
- DiscreteDistr
- def variance: Double
- 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
- Definition Classes
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- def withFilter(p: (Int) => Boolean): Rand[Int]
- Definition Classes
- Rand