PoissonDistribution
Poisson probability distribution object
Description
A PoissonDistribution
object consists of parameters, a
model description, and sample data for a Poisson probability
distribution.
The Poisson distribution is appropriate for applications that involve counting the number of times a random event occurs in a given amount of time, distance, area, etc. If the number of counts follows the Poisson distribution, then the interval between individual counts follows the exponential distribution.
The Poisson distribution uses the following parameters.
Parameter | Description | Support |
---|---|---|
lambda | Mean |
Creation
There are several ways to create a PoissonDistribution
probability
distribution object.
Create a distribution with specified parameter values using
makedist
.Fit a distribution to data using
fitdist
.Interactively fit a distribution to data using the Distribution Fitter app.
Properties
Object Functions
cdf | Cumulative distribution function |
gather | Gather properties of Statistics and Machine Learning Toolbox object from GPU |
icdf | Inverse cumulative distribution function |
iqr | Interquartile range of probability distribution |
mean | Mean of probability distribution |
median | Median of probability distribution |
negloglik | Negative loglikelihood of probability distribution |
paramci | Confidence intervals for probability distribution parameters |
pdf | Probability density function |
plot | Plot probability distribution object |
proflik | Profile likelihood function for probability distribution |
random | Random numbers |
std | Standard deviation of probability distribution |
truncate | Truncate probability distribution object |
var | Variance of probability distribution |
Examples
Extended Capabilities
Version History
Introduced in R2013a