Showing papers on "Dendrogram published in 1988"
TL;DR: The Fowlkes–Mallows statistic, which is a measure of the degree of similarity between two dendrograms, can be used to test the null hypothesis that two dENDrograms are unrelated and can be usefully employed in the systematic comparison of a dependent dendrogram and covariate d endrogram.
Abstract: When interpreting the results of a cluster analysis, it is important to understand why specific clustering patterns arise. Comparison of a "dependent" dendrogram with a second, independently determ...
19 citations
TL;DR: Eight areas in four European countries were characterized by thirty-nine climatic variables and the mean Euclidean distance between each pair of areas was calculated, resulting in a dendrogram of climatic relationships among the eight areas.
Abstract: Eight areas in four European countries (Italy, Yugoslavia, Bulgaria, Czechoslovakia) were characterized by thirty-nine climatic variables. The data were standardized by transformation, and the mean Euclidean distance between each pair of areas was calculated. The matrix of distance values was then subjected to cluster analysis and the results were represented as a dendrogram of climatic relationships among the eight areas. This method is also applicable to a mesoclimatic comparison of localities, or to a more complex numerical comparison and classification of climates over a wide range of regions.
13 citations
TL;DR: The results plus earlier ones suggest the probable importance of patterns of dispersal and establishment, inbreeding, and the geographic scale of comparison, as well as selection, for the patterns observed.
Abstract: Maternal genotypes and three morphometric data sets (cone morphology, short shoot needle cross-sectional anatomy and shape) are available for samples (N = 8 to 11) from two pop- ulations of tamarack from each of five provenance regions in northern Ontario (North Bay, Kenogami R., Thunder Bay, Fort Frances, Red Lake). Data sets were compared using multivariate methods, including canonical variates analysis and a permutation test for resemblance matrix independence. Data sets were represented as dendrograms based on matrices of distances between populations to test the congruence of data sets with the geographic distances between populations, as well as with each other. The distance functions used were chord distance and Nei's genetic distance calculated from genotype data, Euclidean distances calculated from morphometric data (previously ranged if not commensurate), and Mahalanobis' generalized distances calculated for each data set from pop- ulation centroid multi-group principal components analysis scores. Average-linkage was the single sorting algorithm used for clustering. Dendrograms were compared using five descriptors of their structure that were summarized by means of principal coordinates analysis of the Euclidean distances between dendrograms. The effect of data set on resemblances between dendrograms is considerably greater than that of distance function. Populations from the same region tend to resemble each other less than do populations from different regions, with respect to cone and genetic data; only the needle data were appreciably congruent with the geographic relationships. These results plus earlier ones suggest the probable importance of patterns of dispersal and establishment, inbreeding, and the geographic scale of comparison, as well as selection, for the patterns observed.
9 citations