By László Orlóci (auth.)
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Extra resources for Multivariate Analysis in Vegetation Research
3 Sampie Space Let us consider the data in Table 2-1. These data represent our sampie on Table 2-1. 6 1 2 3 4 5 which an analysis is to be performed. We shall use symbol p to designate the number of species (p =3) and symbol n to signify the number of quadrats (n = 5 in the present example). We should note that in more realistic sampies there may be many more species and a greater number of quadrats than p or n in the present sampie. The raw data in Table 2-1 can be presented in matrix form such as Each row in X describes a species and each column holds values which signify performance in one quadrat.
7795 In this example we used data which consist of discrete symbols. It was natural to identify the different symbols as c1ass symbols when we constructed the frequency distributions. A similar procedure could be followed in the case of continuous data, but with modification; the frequency c1asses would have to be defmed as non-overlapping intervals. 19). Relative frequencies and the average information are sometimess less convenient for handling than their fh. multiple, I(Fh) = fh. H(Ph) = - "Lfhj lnfhj/fh.
E. 2) represents an example. This represents a 47 metric, has a consistent scale of measure, and never will fail to form Euclidean triangles. We shall consider the implications of achanging scale in the resemblance function further in a section later in this chapter. 6 A Probabilistic Similarity Index The resemblance measures which we considered so far define the likeness of objects as a composite of individual bits of resemblance values, each contributed by a different variable. In such adefInition the resemblance of a given pair of objects is completely independent from the resemblance of any other pair in the sampie.
Multivariate Analysis in Vegetation Research by László Orlóci (auth.)