unidrnd

Random numbers from discrete uniform distribution

Description

example

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.

example

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.

example

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

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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

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

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

Example: unidrnd(10)

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 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

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

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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.