Distribution

Type Members

sealed abstract class Coin extends AnyRef

Discrete distributions
Discrete distributions

Definition Classes
Distributions

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def F(d1: Int, d2: Int): Distribution[Double]

Definition Classes
Distributions
object H extends Coin with Product with Serializable

Definition Classes
Distributions
object T extends Coin with Product with Serializable

Definition Classes
Distributions
def always[A](value: A): Distribution[A]

Definition Classes
Distributions
final def asInstanceOf[T0]: T0

Definition Classes
Any
def bernoulli(p: Double = 0.5): Distribution[Int]

Definition Classes
Distributions
def beta(a: Double, b: Double): Distribution[Double]

Definition Classes
Distributions
def biasedCoin(p: Double): Distribution[Coin]

Definition Classes
Distributions
def binomial(p: Double, n: Int): Distribution[Int]

Definition Classes
Distributions
def cauchy: Distribution[Double]

Definition Classes
Distributions
def chi2(n: Int): Distribution[Double]

Definition Classes
Distributions
def chi2test[A, B](d: Distribution[(A, B)]): Double

Determine if a joint probability distribution is composed of 2 independent events.
Determine if a joint probability distribution is composed of 2 independent events. Uses the G-test: http://en.wikipedia.org/wiki/G-test

Definition Classes
Distributions
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def coin: Distribution[Coin]

Definition Classes
Distributions
def d(n: Int): Distribution[Int]

Definition Classes
Distributions
def dice(n: Int): Distribution[List[Int]]

Definition Classes
Distributions
def die: Distribution[Int]

Definition Classes
Distributions
def dirichlet(alphas: List[Double]): Distribution[List[Double]]

Definition Classes
Distributions
def discrete[A](weightedValues: (A, Double)*): Distribution[A]

Definition Classes
Distributions
def discreteUniform[A](values: Iterable[A]): Distribution[A]

Definition Classes
Distributions
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def exponential(l: Double): Distribution[Double]

Definition Classes
Distributions
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
def freeze[A](d: Distribution[A], sampleSize: Int = 100000): Distribution[A]

"Freeze" a distribution by taking a sample and serving values out of that sample at random.
"Freeze" a distribution by taking a sample and serving values out of that sample at random. Useful for when a distribution is expensive to compute and is being sampled from repeatedly.

Definition Classes
Distributions
def gamma(k: Double, theta: Double): Distribution[Double]

Definition Classes
Distributions
def geometric(p: Double): Distribution[Int]

Definition Classes
Distributions
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def hashCode(): Int

Definition Classes
AnyRef → Any
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
def ksTest[A](d1: Distribution[A], d2: Distribution[A])(implicit ord: Ordering[A]): Double

Tests if two probability distributions are the same using the Kolmogorov-Smirnov test.
Tests if two probability distributions are the same using the Kolmogorov-Smirnov test. The distributions are unlikely to be the same (p < 0.05) if the value is greater than 1.35 and very unlikely (p < 0.001) if the value is greater than 1.95.

Definition Classes
Distributions
def laplace(b: Double): Distribution[Double]

Definition Classes
Distributions
def lognormal: Distribution[Double]

Definition Classes
Distributions
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def negativeBinomial(p: Double, r: Int): Distribution[Int]

Definition Classes
Distributions
object normal extends Distribution[Double]

Definition Classes
Distributions
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def pareto(a: Double, xm: Double = 1.0): Distribution[Double]

Definition Classes
Distributions
def poisson(lambda: Double): Distribution[Int]

Definition Classes
Distributions
def sequence[T](ds: List[Distribution[T]]): Distribution[List[T]]

Definition Classes
Distributions
def students_t(df: Int): Distribution[Double]

Definition Classes
Distributions
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def tf(p: Double = 0.5): Distribution[Boolean]

Definition Classes
Distributions
def toString(): String

Definition Classes
AnyRef → Any
object uniform extends Distribution[Double]

Continuous distributions
Continuous distributions

Definition Classes
Distributions
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
def weibull(l: Double, k: Double): Distribution[Double]

Definition Classes
Distributions
def zipf(s: Double, n: Int): Distribution[Int]

Definition Classes
Distributions

Related Docs: trait Distribution | package probability_monad

object Distribution extends Distributions

Type Members

sealed abstract class Coin extends AnyRef

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

def F(d1: Int, d2: Int): Distribution[Double]

object H extends Coin with Product with Serializable

object T extends Coin with Product with Serializable

def always[A](value: A): Distribution[A]

final def asInstanceOf[T0]: T0

def bernoulli(p: Double = 0.5): Distribution[Int]

def beta(a: Double, b: Double): Distribution[Double]

def biasedCoin(p: Double): Distribution[Coin]

def binomial(p: Double, n: Int): Distribution[Int]

def cauchy: Distribution[Double]

def chi2(n: Int): Distribution[Double]

def chi2test[A, B](d: Distribution[(A, B)]): Double

def clone(): AnyRef

def coin: Distribution[Coin]

def d(n: Int): Distribution[Int]

def dice(n: Int): Distribution[List[Int]]

def die: Distribution[Int]

def dirichlet(alphas: List[Double]): Distribution[List[Double]]

def discrete[A](weightedValues: (A, Double)*): Distribution[A]

def discreteUniform[A](values: Iterable[A]): Distribution[A]

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def exponential(l: Double): Distribution[Double]

def finalize(): Unit

def freeze[A](d: Distribution[A], sampleSize: Int = 100000): Distribution[A]

def gamma(k: Double, theta: Double): Distribution[Double]

def geometric(p: Double): Distribution[Int]

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

def ksTest[A](d1: Distribution[A], d2: Distribution[A])(implicit ord: Ordering[A]): Double

def laplace(b: Double): Distribution[Double]

def lognormal: Distribution[Double]

final def ne(arg0: AnyRef): Boolean

def negativeBinomial(p: Double, r: Int): Distribution[Int]

object normal extends Distribution[Double]

final def notify(): Unit

final def notifyAll(): Unit

def pareto(a: Double, xm: Double = 1.0): Distribution[Double]

def poisson(lambda: Double): Distribution[Int]

def sequence[T](ds: List[Distribution[T]]): Distribution[List[T]]

def students_t(df: Int): Distribution[Double]

final def synchronized[T0](arg0: ⇒ T0): T0

def tf(p: Double = 0.5): Distribution[Boolean]

def toString(): String

object uniform extends Distribution[Double]

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

def weibull(l: Double, k: Double): Distribution[Double]

def zipf(s: Double, n: Int): Distribution[Int]

Inherited from Distributions

Inherited from AnyRef

Inherited from Any

Ungrouped