Star plots

It is important to remember at this point that the metallicities for the two samples of stars plotted in Fig. 1 were derived using exactly the same techniques, and are thus both in the same scale (see [19]). Also, in the CORALIE planet search sample we have never used the stellar [Fe/H] as a criterion to chose a star. The comparison shown in Fig. 1 is thus not sample-biased. Finally, and as shown in [21], the precision in the derived radial-velocities is not a strong function of the stellar metallicity. The observed increasing frequency of planets with increasing [Fe/H] is thus also not due to any bias in the planet searches. 

Most applications require standardization and involve the potential hazard of distortion of the objects. The recognized similarities must, therefore, be proved with statistical methods. It is very dangerous to cut single features or to reduce the data set. This leads to a change of the data basis on which the standardization will be performed. A comparison with previously computed stars thus becomes impossible. Fig. 5-7 demonstrates a star plot with feature standardization for the example of the PAH in river sediments. Highly loaded sampling points are characterized by big stars and vice versa and similar patterns by similar stars. Similarities in the PAH patterns are particularly apparent for the last five objects. 

Profile plotting is a similar technique to the construction of star plots. Features are arranged as bars in single diagrams for each object. Bars may also be connected by lines. 

Fig. 5-7. Star plot of PAH in 45 selected river sediments from Thuringia, feature standardization.

In the CHERNOFF faces representation, eachparameter corresponds to one feature. Each face is one object. The CHERNOFF faces of the seven PAH in river sediments after feature standardization are demonstrated in Fig. 5-8. The information is the same as that represented in Fig. 5-7 by star plots but conclusions to be drawn are not so clear. 

Star-plots present an alternative means of displaying the same data (Figure 11), with each ray size proportional to individual analyte concentrations. 

Figure 11 Star plots of data from Table 11...

Figure 7.1 Integrative biomarker index as star plots. The integrated biomarker response is obtained from the sum of areas of each biomarker in the test battery. For the spatial survey, it can be observed that sites 1 and 4 are more stressed or affected than the other sites. The general response of biomarkers can be appraised in temporal settings where changes are observed between sites over time.

Fig. 5. Star plots showing the average relative compositions (from Table 4) of each water type.

Budsaba, K., Smith, C.E., and Riviere, J.E., Compass plots a combination of star plot and analysis of means (ANOM) to visualize significant interactions in complex toxicology studies, Toxicol. Methods, 10, 313-332, 2000. 

This intensity is made of two terms one is the scattering by the centers O of the copolymers and the other the contribution of the structure of the copolymer. The separation of these terms is not difficult to perform at large q (q H > 1 ) since the copolymer term vanishes rapidly when q increases. As an example, we have considered in Fig.(5) the case of a four-arms star, plotting ijq) as function of q. The curve 1 corresponds to S(q) =0 it is the contribution of the copolymer term and reaches a plateau. Curve 2 corresponds to an Ornstein Zernicke scattering function for J q) One sees clearly the q tail. This shows that, if there is a fractal exponent, it is theoretically possible to measure it. 

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