Packages

c

scalation.random

Multinomial

case class Multinomial(p: Array[Double] = Array (.4, .7, 1.0), n: Int = 5, stream: Int = 0) extends VariateVec with Product with Serializable

The Multinomial class generates random variate vectors following the multinomial distribution. This discrete RV models the multinomial trials, which generalize Bernoulli trials ({0, 1} to the case where the outcome is in {0, 1, ..., k-1}.

p

array of cumulative probabilities as CDF values

n

the number of independent trials

stream

the random number stream

See also

http://www.math.uah.edu/stat/bernoulli/Multinomial.html

Linear Supertypes
Serializable, Serializable, Product, Equals, VariateVec, Error, AnyRef, Any
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  1. Multinomial
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. VariateVec
  7. Error
  8. AnyRef
  9. Any
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Instance Constructors

  1. new Multinomial(p: Array[Double] = Array (.4, .7, 1.0), n: Int = 5, stream: Int = 0)

    p

    array of cumulative probabilities as CDF values

    n

    the number of independent trials

    stream

    the random number stream

Value Members

  1. def discrete: Boolean

    Determine whether the distribution is discrete or continuous.

    Determine whether the distribution is discrete or continuous.

    Definition Classes
    VariateVec
  2. final def flaw(method: String, message: String): Unit

    Show the flaw by printing the error message.

    Show the flaw by printing the error message.

    method

    the method where the error occurred

    message

    the error message

    Definition Classes
    Error
  3. def gen: VectoD

    Determine the next random double vector for the particular distribution.

    Determine the next random double vector for the particular distribution.

    Definition Classes
    MultinomialVariateVec
  4. def igen: VectoI

    Determine the next random integer vector for the particular distribution.

    Determine the next random integer vector for the particular distribution. It is only valid for discrete random variates.

    Definition Classes
    MultinomialVariateVec
  5. val mean: VectoD
    Definition Classes
    MultinomialVariateVec
  6. val n: Int
  7. val p: Array[Double]
  8. def pf(z: VectoD): Double

    Compute the probability function (pf): The probability density function (pdf) for continuous RVV's or the probability mass function (pmf) for discrete RVV's.

    Compute the probability function (pf): The probability density function (pdf) for continuous RVV's or the probability mass function (pmf) for discrete RVV's.

    z

    the mass point/vector whose probability is sought

    Definition Classes
    MultinomialVariateVec
  9. val stream: Int