class Bernoulli extends DiscreteDistr[Boolean] with Moments[Double, Double]
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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: Boolean): Double
Returns the unnormalized value of the measure
Returns the unnormalized value of the measure
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- DiscreteDistr → Density
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final
def
asInstanceOf[T0]: T0
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def
condition(p: (Boolean) ⇒ Boolean): Rand[Boolean]
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- Rand
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def
draw(): Boolean
Gets one sample from the distribution.
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def
drawOpt(): Option[Boolean]
Overridden by filter/map/flatmap for monadic invocations.
Overridden by filter/map/flatmap for monadic invocations. Basically, rejeciton samplers will return None here
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- Rand
- def entropy: Double
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
filter(p: (Boolean) ⇒ Boolean): Rand[Boolean]
- Definition Classes
- Rand
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def
flatMap[E](f: (Boolean) ⇒ 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
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def
foreach(f: (Boolean) ⇒ 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
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def
get(): Boolean
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final
def
getClass(): Class[_]
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hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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def
logApply(x: Boolean): Double
Returns the log unnormalized value of the measure
Returns the log unnormalized value of the measure
- Definition Classes
- DiscreteDistr → Density
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def
logProbabilityOf(x: Boolean): Double
- Definition Classes
- DiscreteDistr
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def
map[E](f: (Boolean) ⇒ 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
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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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def
probabilityOf(b: Boolean): Double
Returns the probability of that draw.
Returns the probability of that draw.
- Definition Classes
- Bernoulli → DiscreteDistr
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def
sample(n: Int): IndexedSeq[Boolean]
Gets n samples from the distribution.
Gets n samples from the distribution.
- Definition Classes
- Rand
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def
sample(): Boolean
Gets one sample from the distribution.
Gets one sample from the distribution. Equivalent to get()
- Definition Classes
- Rand
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def
samples: Iterator[Boolean]
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
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def
samplesVector[U >: Boolean](size: Int)(implicit m: ClassTag[U]): DenseVector[U]
Return a vector of samples.
Return a vector of samples.
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- Rand
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
- Definition Classes
- Bernoulli → AnyRef → Any
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def
unnormalizedLogProbabilityOf(x: Boolean): Double
- Definition Classes
- DiscreteDistr
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def
unnormalizedProbabilityOf(x: Boolean): 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
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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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final
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wait(): Unit
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def
withFilter(p: (Boolean) ⇒ Boolean): Rand[Boolean]
- Definition Classes
- Rand