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**[[maximum spacing estimation]]
**method of [[L-moment]]s<ref>{{cite journal | last=Hosking | first=J.R.M. | year=1990 | title=L-moments: analysis and estimation of distributions using linear combinations of order statistics | journal=Journal of the Royal Statistical Society, Series B | volume=52 | pages=105–124 | jstor=2345653}}</ref>
**[[Maximum likelihood]] method<ref>{{cite journal | last = Aldrich | first = John | title = R. A. Fisher and the making of maximum likelihood 1912–1922 | year = 1997 | journal = Statistical Science | volume = 12 | issue = 3 | pages = 162–176 | doi = 10.1214/ss/1030037906 | mr = 1617519 | ref = citeref Aldrich1997| doi-access = free }}</ref>
::{| class="wikitable"
| bgcolor="white" | ''For example, the parameter <math>\mu</math> (the'' ''[[expected value|expectation]]) can be estimated by the [[Arithmetic mean|mean]] of the data and the parameter <math>\sigma^2</math> (the [[variance]]) can be estimated from the [[standard deviation]] of the data. The mean is found as <math>m=\sum{X}/n</math>, where <math>X</math> is the data value and <math>n</math> the number of data, while the standard deviation is calculated as <math>s=\sqrt{\frac{1}{n-1}\sum{(X-m)^2}}</math>. With these parameters many distributions, e.g. the normal distribution, are completely defined.''
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