random - Random numbers

Syntax

Y = random(name,A) Y = random(name,A,B) Y = random(name,A,B,C) Y = random(...,m,n,...) Y = random(...,[m,n,...])

Description

Y = random(name,A) where name is the name of a distribution that takes a single parameter, returns random numbers Y from the one-parameter family of distributions specified by name. Parameter values for the distribution are given in A.

Y is the same size as A.

Y = random(name,A,B) returns random numbers Y from a two-parameter family of distributions. Parameter values for the distribution are given in A and B.

If A and B are arrays, they must be the same size. If either A or B are scalars, they are expanded to constant matrices of the same size.

Y = random(name,A,B,C) returns random numbers Y from a three-parameter family of distributions. Parameter values for the distribution are given in A, B, and C.

If A, B, and C are arrays, they must be the same size. If any of A, B, or C are scalars, they are expanded to constant matrices of the same size.

Y = random(...,m,n,...) or Y = random(...,[m,n,...]) returns an m-by-n-by... matrix of random numbers.

If any of A, B, or C are arrays, then the specified dimensions must match the common dimensions of A, B, and C after any necessary scalar expansion.

The following table denotes the acceptable strings for name, as well as the parameters for that distribution:

`name`	Distribution	Input Parameter A	Input Parameter B	Input Parameter C
`'beta'`	Beta Distribution	`a`	`b`	—
`'bino'`	Binomial Distribution	`n`: number of trials	`p`: probability of success for each trial	—
`'chi2'`	Chi-Square Distribution	ν: degrees of freedom	—	—
`'exp'`	Exponential Distribution	`μ`: mean	—	—
`'ev'`	Extreme Value Distribution	`μ`: location parameter	σ: scale parameter	—
`'f'`	F Distribution	ν`1`: numerator degrees of freedom	ν`2`: denominator degrees of freedom	—
`'gam'`	Gamma Distribution	`a`: shape parameter	`b`: scale parameter	—
`'gev'`	Generalized Extreme Value Distribution	`K`: shape parameter	`μ`: location parameter	σ: scale parameter
`'gp'`	Generalized Pareto Distribution	`k`: tail index (shape) parameter	σ: scale parameter	`μ`: threshold (location) parameter
`'geo'`	Geometric Distribution	`p`: probability parameter	—	—
`'hyge'`	Hypergeometric Distribution	`M`: size of the population	`K`: number of items with the desired characteristic in the population	`n`: number of samples drawn
`'logn'`	Lognormal Distribution	`μ`	σ	—
`'nbin'`	Negative Binomial Distribution	`r`: number of successes	`p`: probability of success in a single trial	—
`'ncf'`	Noncentral F Distribution	ν`1`: numerator degrees of freedom	ν`2`: denominator degrees of freedom	δ: noncentrality parameter
`'nct'`	Noncentral t Distribution	ν: degrees of freedom	δ: noncentrality parameter	—
`'ncx2'`	Noncentral Chi-Square Distribution	ν: degrees of freedom	δ: noncentrality parameter	—
`'norm'`	Normal Distribution	`μ`: mean	σ: standard deviation	—
`'poiss'`	Poisson Distribution	λ: mean	—	—
`'rayl'`	Rayleigh Distribution	`b`: scale parameter	—	—
`'t'`	Student's t Distribution	ν: degrees of freedom	—	—
`'unif'`	Uniform Distribution (Continuous)	`a`: lower endpoint (minimum)	`b`: upper endpoint (maximum)	—
`'unid'`	Uniform Distribution (Discrete)	`N`: maximum observable value	—	—
`'wbl'`	Weibull Distribution	`a`: scale parameter	`b`: shape parameter	—

Examples

Generate a 2-by-4 array of random values from the normal distribution with mean 0 and standard deviation 1:

x1 = random('Normal',0,1,2,4)
x1 =
  1.1650  0.0751  -0.6965  0.0591
  0.6268  0.3516  1.6961  1.7971

The order of the parameters is the same as for normrnd.

Generate a single random value from Poisson distributions with rate parameters 1, 2, ..., 6, respectively:

x2 = random('Poisson',1:6,1,6)
x2 =
   0   0   1   2   5   7

random - Random numbers

Syntax

Description

Examples

See Also

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