BernoulliProcess
represents a Bernoulli process with event probability p.
Details
- BernoulliProcess is a discrete-time and discrete-state process.
- BernoulliProcess at a fixed instant of time is a Bernoulli random variate with parameter p.
- BernoulliProcess can be used with such functions as Mean, PDF, Probability, and RandomFunction.
Examples
open allclose allScope (11)
Basic Uses (5)
Process Slice Properties (6)
Univariate SliceDistribution:
Univariate slice probability density:
Multi-time slice distribution:
Higher-order PDF:
Compute the expectation of an expression:
Calculate the probability of an event:
Skewness does not depend on time:
BernoulliProcess is symmetric for p=1/2:
Kurtosis does not depend on time:
The minimum value of kurtosis:
CentralMoment and its generating function:
FactorialMoment has no closed form for symbolic order:
Cumulant and its generating function:
Properties & Relations (5)
Bernoulli process is weakly stationary:
Bernoulli process has a well-defined StationaryDistribution:
Transition probability does not depend on the current state:
A BinomialProcess is the sum of a BernoulliProcess with :
Compare to the BinomialProcess:
Bernoulli process satisfies the law of large numbers:
Text
Wolfram Research (2012), BernoulliProcess, Wolfram Language function, https://reference.wolfram.com/language/ref/BernoulliProcess.html.
CMS
Wolfram Language. 2012. "BernoulliProcess." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/BernoulliProcess.html.
APA
Wolfram Language. (2012). BernoulliProcess. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/BernoulliProcess.html