How to random sample a 2-parameter weibull distribution in python

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抹茶落季
抹茶落季 2021-01-19 20:54

I was wondering how to generate a random weibull distribution with 2-parameter (lambda, k) in python. I know that numpy has a numpy.random.weibull, but it only accepts the <

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  • 2021-01-19 21:06

    Well, if you sample a number from weibull distribution with scale parameter missing (which assumes scale is equal to 1), then to get it scale multiply by lambda.

    x = numpy.random.weibull(a)
    return lambda*x
    
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  • 2021-01-19 21:14

    Severin Pappadeux's answer is probably the simplest way to include the scale parameter. An alternative is to use scipy.stats.weibull_min. weibull_min has three parameters: shape, location and scale. You only want the shape and scale, so you would set the location to 0.

    from scipy.stats import weibull_min
    
    n = 100     # number of samples
    k = 2.4     # shape
    lam = 5.5   # scale
    
    x = weibull_min.rvs(k, loc=0, scale=lam, size=n)
    
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