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POHow do I get a lognormal distribution in Python with Mu and Sigma?
 

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  1. POHow do I get a lognormal distribution in Python with Mu and Sigma?
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    <p>I have been trying to get the result of a <a href="http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.lognorm.html" rel="nofollow noreferrer">lognormal</a> distribution using <a href="http://www.scipy.org/" rel="nofollow noreferrer">Scipy</a>. I already have the Mu and Sigma, so I don't need to do any other prep work. If I need to be more specific (and I am trying to be with my limited knowledge of stats), I would say that I am looking for the cumulative function (cdf under Scipy). The problem is that I can't figure out how to do this with just the mean and standard deviation on a scale of 0-1 (ie the answer returned should be something from 0-1). I'm also not sure which method from <strong>dist</strong>, I should be using to get the answer. I've tried reading the documentation and looking through SO, but the relevant questions (like <a href="https://stackoverflow.com/questions/8747761/scipy-lognormal-distribution-parameters">this</a> and <a href="https://stackoverflow.com/questions/1154378/how-to-run-statistics-cumulative-distribution-function-and-probablity-density-fu">this</a>) didn't seem to provide the answers I was looking for.</p> <p>Here is a code sample of what I am working with. Thanks.</p> <pre><code>from scipy.stats import lognorm stddev = 0.859455801705594 mean = 0.418749176686875 total = 37 dist = lognorm.cdf(total,mean,stddev) </code></pre> <p><strong>UPDATE:</strong></p> <p>So after a bit of work and a little research, I got a little further. But I still am getting the wrong answer. The new code is below. According to R and Excel, the result should be <em>.7434</em>, but that's clearly not what is happening. Is there a logic flaw I am missing?</p> <pre><code>dist = lognorm([1.744],loc=2.0785) dist.cdf(25) # yields=0.96374596, expected=0.7434 </code></pre> <p><strong>UPDATE 2:</strong> Working lognorm implementation which yields the correct <strong>0.7434</strong> result.</p> <pre><code>def lognorm(self,x,mu=0,sigma=1): a = (math.log(x) - mu)/math.sqrt(2*sigma**2) p = 0.5 + 0.5*math.erf(a) return p lognorm(25,1.744,2.0785) &gt; 0.7434 </code></pre>
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    1. USEric Lubow
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    1. COcould you explain what do you understand for "the result of a distribution" ?
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    2. CO@joaquin I added a code sample that shows what I have and what I expect it to yield.
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    3. CO@EricLubow: I think you might be misunderstanding what mean and stddev mean in this case. For the lognormal distribution they are the mean and stddev *of the logarithm of the variable*. If a variable is lognormally distributed, it implies that the logarithm of the variable is normally distributed.
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