How to generate random number from cumulative distribution function (CDF) in Matlab

Hi everyone,

Similar to R program, I'm looking for a code in Matlab that I can generate a set of random number with a specific mean (M) and standard deviation (sd).

R code to generate random number with normal distribution from CDF:

> pnorm(1.96, mean=0, sd=1)
[1] 0.9750021

Answer 1

[Image Analyst]

For the more general case of an arbitrary CDF , you have to use inverse transform sampling. Attached is an example for generating a Rayleigh transform.

Answer 2

[Image Analyst]

Did you see the example in the help for randn()? Here it is:

Random Numbers from Normal Distribution with Specific Mean and Variance

This example shows how to create an array of 
random floating-point numbers that are drawn 
from a normal distribution having a mean of 500 and variance of 25.

The randn function returns a sample of random numbers from a normal distribution 
with mean 0 and variance 1. The general theory of random variables
states that if x is a random variable whose mean is μ
x
 and variance is σ
2
x
, then the random variable, y, defined by y=ax+b,
where a and b are constants, has mean μ
y
=aμ
x
+b and variance σ
2
y
=a
2
σ
2
x
. You can apply this concept to get a sample of 
normally distributed random numbers with mean 500 and variance 25.

First, initialize the random number generator to make the results in this example repeatable.

rng(0,'twister');
Create a vector of 1000 random values 
drawn from a normal distribution with a mean of 500 
and a standard deviation of 5.

a = 5;
b = 500;
y = a.*randn(1000,1) + b;

Answer 3

[Sean de Wolski]

doc slicesample
doc random

[Moe]

with this command:

rnd = slicesample(initial,nsamples,'pdf',pdf)

Can you give me a simple example of it?