pearsrnd
Pearson system random numbers
Syntax
r = pearsrnd(mu,sigma,skew,kurt,m,n)
r = pearsrnd(mu,sigma,skew,kurt)
r = pearsrnd(mu,sigma,skew,kurt,m,n,...)
r
= pearsrnd(mu,sigma,skew,kurt,[m,n,...])
[r,type] = pearsrnd(...)
[r,type,coefs] = pearsrnd(...)
Description
r = pearsrnd(mu,sigma,skew,kurt,m,n)
returns
an m
-by-n
matrix of random numbers
drawn from the distribution in the Pearson system with mean mu
,
standard deviation sigma
, skewness skew
,
and kurtosis kurt
. The parameters mu
, sigma
, skew
,
and kurt
must be scalars.
Note
Because r
is a random sample, its sample
moments, especially the skewness and kurtosis, typically differ somewhat
from the specified distribution moments.
pearsrnd
uses the definition of kurtosis
for which a normal distribution has a kurtosis of 3. Some definitions
of kurtosis subtract 3, so that a normal distribution has a kurtosis
of 0. The pearsrnd
function does not use this
convention.
Some combinations of moments are not valid; in particular, the kurtosis must be greater than the square of the skewness plus 1. The kurtosis of the normal distribution is defined to be 3.
r = pearsrnd(mu,sigma,skew,kurt)
returns
a scalar value.
r = pearsrnd(mu,sigma,skew,kurt,m,n,...)
or r
= pearsrnd(mu,sigma,skew,kurt,[m,n,...])
returns an m
-by-n
-by-...
array.
[r,type] = pearsrnd(...)
returns the type
of the specified distribution within the Pearson system. type
is
a scalar integer from 0
to 7
.
Set m
and n
to 0
to
identify the distribution type without generating any random values.
The seven distribution types in the Pearson system correspond to the following distributions:
0
— Normal distribution1
— Four-parameter beta distribution2
— Symmetric four-parameter beta distribution3
— Three-parameter gamma distribution4
— Not related to any standard distribution. The density is proportional to:(1 + ((x – a)/b)2)–c exp(–d arctan((x – a)/b)).
5
— Inverse gamma location-scale distribution6
— F location-scale distribution7
— Student's t location-scale distribution
[r,type,coefs] = pearsrnd(...)
returns
the coefficients coefs
of the quadratic polynomial
that defines the distribution via the differential equation
Examples
Generate random values from the standard normal distribution:
r = pearsrnd(0,1,0,3,100,1); % Equivalent to randn(100,1)
[r,type] = pearsrnd(0,1,1,4,0,0); r = [] type = 1
References
[1] Johnson, N.L., S. Kotz, and N. Balakrishnan (1994) Continuous Univariate Distributions, Volume 1, Wiley-Interscience, Pg 15, Eqn 12.33.
Extended Capabilities
Version History
Introduced in R2006a