poissrnd

Random numbers from Poisson distribution

Description

example

r = poissrnd(lambda) generates random numbers from the Poisson distribution specified by the rate parameter lambda.

lambda can be a scalar, vector, matrix, or multidimensional array.

example

r = poissrnd(lambda,sz1,...,szN) generates an array of random numbers from the Poisson distribution with the scalar rate parameter lambda, where sz1,...,szN indicates the size of each dimension.

example

r = poissrnd(lambda,sz) generates an array of random numbers from the Poisson distribution with the scalar rate parameter lambda, where vector sz specifies size(r).

Examples

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Generate an array of random numbers from the Poisson distributions. Specify the average rate for each distribution.

lambda = 10:2:20
lambda = 1×6

10    12    14    16    18    20

Generate random numbers from the Poisson distributions.

r = poissrnd(lambda)
r = 1×6

14    13    14     9    14    31

Generate an array of random numbers from one Poisson distribution. Here, the distribution parameter lambda is a scalar.

Use the poissrnd function to generate random numbers from the Poisson distribution with the average rate 20. The function returns one number.

r_scalar = poissrnd(20)
r_scalar = 9

Generate a 2-by-3 array of random numbers from the same distribution by specifying the required array dimensions.

r_array = poissrnd(20,2,3)
r_array = 2×3

13    14    18
26    16    21

Alternatively, specify the required array dimensions as a vector.

r_array = poissrnd(20,[2 3])
r_array = 2×3

22    27    22
25    19    21

Input Arguments

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Rate parameters, specified as a positive value or array of positive values. The rate parameter indicates the average number of events in a given time interval.

Example: 2

Data Types: single | double

Size of each dimension, specified as separate arguments of integers. For example, specifying 5,3,2 generates a 5-by-3-by-2 array of random numbers from the Poisson probability distribution.

If lambda is an array, then the specified dimensions sz1,...,szN must match the dimensions of lambda.

• If you specify a single value sz1, then r is a square matrix of size sz1-by-sz1.

• If the size of any dimension is 0 or negative, then r is an empty array.

• Beyond the second dimension, poissrnd ignores trailing dimensions with a size of 1. For example, poissrnd(5,3,1,1,1) produces a 3-by-1 vector of random numbers from the Poisson distribution with rate parameter 5.

Example: 5,3,2

Data Types: single | double

Size of each dimension, specified as a row vector of integers. For example, specifying [5 3 2] generates a 5-by-3-by-2 array of random numbers from the Poisson probability distribution.

If lambda is an array, then the specified dimensions sz must match the dimensions of lambda.

• If you specify a single value [sz1], then r is a square matrix of size sz1-by-sz1.

• If the size of any dimension is 0 or negative, then r is an empty array.

• Beyond the second dimension, poissrnd ignores trailing dimensions with a size of 1. For example, poissrnd(5,[3,1,1,1]) produces a 3-by-1 vector of random numbers from the Poisson distribution with rate parameter 5.

Example: [5 3 2]

Data Types: single | double

Output Arguments

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Random numbers from the Poisson distribution, returned as a scalar value or an array of scalar values.

Data Types: single | double

Alternative Functionality

• poissrnd is a function specific to Poisson distribution. Statistics and Machine Learning Toolbox™ also offers the generic function random, which supports various probability distributions. To use random, specify the probability distribution name and its parameters. Alternatively, create a PoissonDistribution probability distribution object and pass the object as an input argument. Note that the distribution-specific function poissrnd is faster than the generic function random.

• To generate random numbers interactively, use randtool, a user interface for random number generation.