Editing Student's t-distribution (section)

==Computational methods==
===Monte Carlo sampling===
There are various approaches to constructing random samples from the Student's {{mvar|t}}&nbsp;distribution. The matter depends on whether the samples are required on a stand-alone basis, or are to be constructed by application of a [[quantile function]] to [[uniform]] samples; e.g., in the multi-dimensional applications basis of [[Copula (statistics)|copula-dependency]].{{citation needed|date=July 2011}} In the case of stand-alone sampling, an extension of the [[Box–Muller method]] and its [[Box–Muller transform#Polar form|polar form]] is easily deployed.<ref name=Bailey>{{Cite journal |vauthors=Bailey RW |date=1994 |title=Polar generation of random variates with the {{mvar|t}}&nbsp;distribution |journal=[[Mathematics of Computation]] |volume=62 |issue=206 |pages=779–781 |doi=10.2307/2153537 |jstor=2153537 |bibcode=1994MaCom..62..779B |s2cid=120459654 }}</ref> It has the merit that it applies equally well to all real positive [[degrees of freedom (statistics)|degrees of freedom]], {{mvar|ν}}, while many other candidate methods fail if {{mvar|ν}} is close to zero.<ref name=Bailey/>