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One is the system of lots, which are influential points as distant from some specified points in the horoscopic diagram as two planets are from each other.
Detection of such influential points is therefore essential.
The outlying ROIs appear as influential points in the plots.
Leverage plots were also examined to determine if any influential points existed.
Even for 10 years the impact of influential points can still be high (>30% influence on maximum predicted flows).
Stage one uses computationally efficient regression-theory influence diagnostics to identify the most influential points based on Cook's distance.
During the fitting process, observations that are suspicious (e.g. outliers and/or influential points) may cause problems.
We illustrate the effectiveness of the method in order to identify influential points with two real examples.
All these graphically oriented techniques are suitable for the rapid estimation of influential points, but are generally incapable of solving problems with masking and swamping.
The powerful procedure for the computation of influential points characteristics has been written in Matlab 5.3 and is available from authors.
In the presence of these influential points in the data, Cantoni and Ronchetti (2001) advocated the use of robust estimator over MLE.
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