<p dir="auto">I encounter a problem using the nct.cdf function in scipy.stats!</p>
<p dir="auto">nct.cdf is the t-Student cumulative distribution function, with shape parameters df (degrees of freedom), nc (non central parameter).</p>
<p dir="auto">Curiously enough, this function works well for nc&lt;= 65535</p>
<p dir="auto">YET FOR nc&gt;=65536</p>
<p dir="auto">You will notice that for any x, and for any nc&gt;=65536:</p>
<p dir="auto">nct.cdf(x,df,nc)=1.0 which is completely absurd!</p>
<p dir="auto">For instance:</p>
<p dir="auto">from scipy.stats import nct</p>
<p dir="auto">nct.cdf(45,9,65536) gives 1.0 ????? (It should normally be close to 0)</p>
<p dir="auto">Would any one have a solution to this problem?</p>
<p dir="auto">Is it a limitation of the algorithm or a fortran type overflow?</p>
<p dir="auto">Thank you by advance.</p>
<p dir="auto">From <a href="http://stackoverflow.com/questions/21061921/saturation-of-nct-cdf-for-nc-65536-scipy-stats" rel="nofollow">stackoverflow</a>:</p>
<p dir="auto">"""<br>
I encounter a problem using the nct.cdf function in scipy.stats!</p>
<p dir="auto">nct.cdf is the t-Student cumulative distribution function, with shape parameters df (degrees of freedom), nc (non central parameter).</p>
<p dir="auto">Curiously enough, this function works well for nc&lt;= 65535</p>
<p dir="auto">YET FOR nc&gt;=65536</p>
<p dir="auto">You will notice that for any x, and for any nc&gt;=65536:<br>
nct.cdf(x,df,nc)=1.0 which is completely absurd!</p>
<p dir="auto">For instance:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="from scipy.stats import nct
nct.cdf(45,9,65536) # gives 1.0 ????? (It should normally be close to 0)"><pre class="notranslate"><code class="notranslate">from scipy.stats import nct
nct.cdf(45,9,65536) # gives 1.0 ????? (It should normally be close to 0)
</code></pre></div>
<p dir="auto">"""</p>