<p dir="auto"><em>Original ticket <a href="http://projects.scipy.org/scipy/ticket/1864" rel="nofollow">http://projects.scipy.org/scipy/ticket/1864</a> on 2013-03-11 by <a class="user-mention notranslate" data-hovercard-type="user" data-hovercard-url="/users/josef-pkt/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" href="https://github.com/josef-pkt">@josef-pkt</a>, assigned to <a class="user-mention notranslate" data-hovercard-type="user" data-hovercard-url="/users/rgommers/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" href="https://github.com/rgommers">@rgommers</a>.</em></p>
<p dir="auto">I guess a bug, because _argcheck is not properly defined</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="&gt;&gt;&gt; stats.nct.cdf(-0.5, 10, -0.5)
nan
&gt;&gt;&gt; stats.nct._cdf(-0.5, 10, -0.5)
0.50490799249967822"><pre class="notranslate"><code class="notranslate">&gt;&gt;&gt; stats.nct.cdf(-0.5, 10, -0.5)
nan
&gt;&gt;&gt; stats.nct._cdf(-0.5, 10, -0.5)
0.50490799249967822
</code></pre></div>
<p dir="auto">same value as in R</p>
<p dir="auto">(needed for power of t-test)</p>
<p dir="auto"><em>Original ticket <a href="http://projects.scipy.org/scipy/ticket/1883" rel="nofollow">http://projects.scipy.org/scipy/ticket/1883</a> on 2013-03-29 by trac user Sytse, assigned to <a class="user-mention notranslate" data-hovercard-type="user" data-hovercard-url="/users/rgommers/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" href="https://github.com/rgommers">@rgommers</a>.</em></p>
<p dir="auto">The non-central t-distribution in scipy.stats.distributions accepts a non-centrality parameter with positive values only.</p>
<p dir="auto">From Wikipedia (<a href="http://en.wikipedia.org/wiki/Noncentral_t-distribution" rel="nofollow">http://en.wikipedia.org/wiki/Noncentral_t-distribution</a>):<br>
"If Z is a normally distributed random variable with unit variance and zero mean, and V is a Chi-squared distributed random variable with ν degrees of freedom that is statistically independent of Z, then T=(Z+μ)/sqrt(V/ν) is a noncentral t-distributed random variable with ν degrees of freedom and noncentrality parameter μ. Note that the noncentrality parameter may be negative."</p>
<p dir="auto">Adding a function:[[BR]]</p>
<p dir="auto">def _argcheck(self, df, nc):[[BR]]<br>
return (df &gt; 0)[[BR]]</p>
<p dir="auto">to the class class nct_gen  would completely solve the problem.</p>