Editing Pearson correlation coefficient (section)

===Practical issues===
Under heavy noise conditions, extracting the correlation coefficient between two sets of [[Random variables|stochastic variables]] is nontrivial, in particular where [[Canonical Correlation Analysis]] reports degraded correlation values due to the heavy noise contributions. A generalization of the approach is given elsewhere.<ref>{{cite book |first= N. |last=Moriya |year=2008 |contribution=Noise-related multivariate optimal joint-analysis in longitudinal stochastic processes  |pages=[https://books.google.com/books?id=4XvRgF0QfqkC&pg=PA223 223–260] |editor=Yang, Fengshan  |title=[[Progress in Applied Mathematical Modeling]] |publisher=[[Nova Science Publishers, Inc.]] |isbn=978-1-60021-976-4 }}</ref>

In case of missing data, Garren derived the [[maximum likelihood]] estimator.<ref>{{cite journal |last=Garren |first=Steven T. |date=15 June 1998 |title=Maximum likelihood estimation of the correlation coefficient in a bivariate normal model, with missing data |journal=Statistics & Probability Letters |volume=38 |issue=3 |pages=281–288 |doi=10.1016/S0167-7152(98)00035-2 }}</ref>

Some distributions (e.g., [[stable distribution]]s other than a [[normal distribution]]) do not have a defined variance.