What is marvelous is the camerawork, the editing and the moment-by-moment sequencing of each episode.
2.
In probability theory, the "'method of moments "'is a way of proving convergence in distribution by proving convergence of a sequence of moment sequences.
3.
In " Summation methods and moment sequences I " in 1921, he developed a whole class of summation methods for divergent series, which today are called Hausdorff methods.
4.
Every Hausdorff method is given by a moment sequence; in this context Hausdorff gave an elegant solution of the moment problem for a finite interval, bypassing the theory of continued fractions.
5.
In this way we see that every moment sequence is also a cumulant sequence ( the converse cannot be true, since cumulants of even order e " 4 are in some cases negative, and also because the cumulant sequence of the normal distribution is not a moment sequence of any probability distribution ).
6.
In this way we see that every moment sequence is also a cumulant sequence ( the converse cannot be true, since cumulants of even order e " 4 are in some cases negative, and also because the cumulant sequence of the normal distribution is not a moment sequence of any probability distribution ).
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