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In statistics, Cook's distance or Cook's D is a commonly used estimate of the influence of a data point when performing a least-squares regression analysis. [1] In a practical ordinary least squares analysis, Cook's distance can be used in several ways: to indicate influential data points that are particularly worth checking for validity; or to indicate regions of the design space where it ...
Convolution random number generator; Conway–Maxwell–Poisson distribution; Cook's distance; Cophenetic correlation; Copula (statistics) Cornish–Fisher expansion; Correct sampling; Correction for attenuation; Correlation; Correlation and dependence; Correlation does not imply causation; Correlation clustering; Correlation function ...
Although the raw values resulting from the equations are different, Cook's distance and DFFITS are conceptually identical and there is a closed-form formula to convert one value to the other. [ 3 ] Development
A matrix, has its column space depicted as the green line. The projection of some vector onto the column space of is the vector . From the figure, it is clear that the closest point from the vector onto the column space of , is , and is one where we can draw a line orthogonal to the column space of .
The Moser spindle embedded as a unit distance graph in the plane, together with a seven-coloring of the plane. As a unit distance graph, the Moser spindle is formed by two rhombi with 60 and 120 degree angles, so that the sides and short diagonals of the rhombi form equilateral triangles. The two rhombi are placed in the plane, sharing one of ...
For k = 3, every k-critical graph (that is, every odd cycle) can be generated as a k-constructible graph such that all of the graphs formed in its construction are also k-critical. For k = 8 , this is not true: a graph found by Catlin (1979) as a counterexample to Hajós's conjecture that k -chromatic graphs contain a subdivision of K k , also ...
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It's the third equation that's incorrect: the denominator should be p s^2, not (1+p) s^2. Primrose61 18:52, 11 November 2013 (UTC) []. The denumerator in the second equation should be p * s^2, and in the terms of MSE, s^2 = MSE * n / (n - p), where n is the number of observations, and p is the number of parameters, so the whole equation should be: