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EMPRAND generates random numbers from empirical distribution of data. This is useful when you do not know the distribution type (i.e. normal or uniform), but you have the data and you want to generate random numbers form that data.
The idea is to first construct cumulative distribution function (cdf) from the given data. Then generate uniform random number and interpolate from cdf.
USAGE:
[xr] = emprand(dist) generates single random number from given vector of data values dist.
[xr] = emprand(dist,m) generates m by m matrix of random numbers.
[xr] = emprand(dist,m,n) generates m by n matrix of random numbers.
Examples:
% Generate 1000 random normal numbers as data for EMPRAND
dist = randn(1000,1);
% Now generate 2000 random numbers from this data
xr = emprand(dist,2000,1);
Cite As
Durga Lal Shrestha (2026). Random Number from Empirical Distribution (https://www.mathworks.com/matlabcentral/fileexchange/7976-random-number-from-empirical-distribution), MATLAB Central File Exchange. Retrieved .
Acknowledgements
Inspired: Probability Transformation Explorer
General Information
- Version 1.0.0.0 (3.12 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 | BSD License
|
