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I am trying to obtain stratified random samples from a normal distribution.

On Matlab this is as simple as X = lhsnorm (mu, sigma, n)

Mathworks documentation: https://uk.mathworks.com/help/stats/lhsnorm.html

Is there an equivalent way to do this in python?

OKJN
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  • Possibly helpful? https://stackoverflow.com/questions/12884361/latin-hypercube-sampling-from-a-normal-distribution-python and https://stackoverflow.com/questions/26137195/latin-hypercube-sampling-with-python – DavidG May 04 '18 at 11:14
  • Possible duplicate of [Latin hypercube sampling with python](https://stackoverflow.com/questions/26137195/latin-hypercube-sampling-with-python) – Eolmar May 04 '18 at 11:17
  • Possible duplicate of [Latin Hypercube Sampling from a normal distribution (Python)](https://stackoverflow.com/questions/12884361/latin-hypercube-sampling-from-a-normal-distribution-python) – Sardar Usama May 05 '18 at 21:14

1 Answers1

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use numpy package and type:

np.random.normal(mu, sigma, n)

MR.Mohebian
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