unidrnd

Random numbers from discrete uniform distribution

Syntax

r = unidrnd(n)

r = unidrnd(n,sz1,...,szN)

r = unidrnd(n,sz)

Description

r = unidrnd(n) generates random numbers from the discrete uniform distribution specified by its maximum value n.

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

r = unidrnd(n,sz1,...,szN) generates an array of random numbers from the discrete uniform distribution with the scalar maximum value n, where sz1,...,szN indicates the size of each dimension.

r = unidrnd(n,sz) generates an array of random numbers from the discrete uniform distribution with the scalar maximum value n, where vector sz specifies size(r).

Examples

Array of Random Numbers from Several Discrete Uniform Distributions

Generate an array of random numbers from the discrete uniform distributions. For each distribution, specify its maximum value.

Specify the maximum values of the distributions.

n = 1:10:100;

Generate random numbers from the discrete uniform distributions.

r = unidrnd(n)

r = 1×10

     1    10     3    29    26     5    17    39    78    88

Array of Random Numbers from One Discrete Uniform Distribution

Generate an array of random numbers from one discrete uniform distribution. Here, the maximum value n is a scalar.

Use the unidrnd function to generate random numbers from the discrete uniform distribution with the maximum value 100. The function returns one number.

R_scalar = unidrnd(100)

R_scalar = 82

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

R_array = unidrnd(100,2,3)

R_array = 2×3

    91    92    10
    13    64    28

Alternatively, specify the required array dimensions as a vector.

R_array = unidrnd(100,[2,3])

R_array = 2×3

    55    97    98
    96    16    96

Input Arguments

n — Maximum value

positive integer | array of positive integers

Maximum value, specified as a positive integer or array of positive integers.

Example: unidrnd(10)

Data Types: single | double

sz1,...,szN — Size of each dimension (as separate arguments)

integers

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 discrete uniform distribution.

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

• 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, unidrnd ignores trailing dimensions with a size of 1. For example, unidrnd(n,3,1,1,1) produces a 3-by-1 vector of random numbers.

Example: 5,3,2

Data Types: single | double

sz — Size of each dimension (as a row vector)

row vector of integers

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 discrete uniform distribution.

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

• 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, unidrnd ignores trailing dimensions with a size of 1. For example, unidrnd(n,[3 1 1 1]) produces a 3-by-1 vector of random numbers.

Example: [5 3 2]

Data Types: single | double

Output Arguments

r — Random numbers from discrete uniform distribution

scalar value | array of scalar values

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

Data Types: single | double

Alternative Functionality

• unidrnd is a function specific to discrete uniform 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. Note that the distribution-specific function unidrnd is faster than the generic function random.

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

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

The generated code can return a different sequence of numbers than MATLAB^® if either of the following is true:

• The output is nonscalar.

• An input parameter is invalid for the distribution.

For more information on code generation, see Introduction to Code Generation and General Code Generation Workflow.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).