研究表明未来6个月有70%可能有Recession

https://www.cnbc.com/2020/02/05/70percent-chance-of-recession-in-next-six-months-study-from-mit-and-state-street-finds.html

这个方法似乎有点类似于模式分析。

Seriously？ 有点像要发生。

 

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The Mahalanobis distance is a measure of the distance between a point P and a distribution D, introduced by P. C. Mahalanobis in 1936.^[1] It is a multi-dimensional generalization of the idea of measuring how many standard deviations away P is from the mean of D. This distance is zero if P is at the mean of D, and grows as P moves away from the mean along each principal component axis. If each of these axes is re-scaled to have unit variance, then the Mahalanobis distance corresponds to standard Euclidean distance in the transformed space. The Mahalanobis distance is thus unitless and scale-invariant, and takes into account the correlations of the data set.