the relationship between topography, soil factors, and distribution of ecological vegetation groups in the nodoushan arid rangelands of yazd province (iran) was investigated. the present species were recorded in each vegetation group using a randomized-systematic sampling method. plant cover and density were estimated quantitatively using the transect and quadrate methods, and the two-way indic...

in this study multivariate statistical analysis are used to characterize relationships between hydrochemical properties ofthermal and non-thermal springs. four factors for thermal waters and two for non-thermal springs were extracted basedon factor analysis. in thermal springs, the first factor showed high loading on ca, mg, na and k and this factor wasinterpreted as leaching of cations in the ...

The recent developments by considering a rather unexpected application of the theory of Independent component analysis (ICA) found in outlier detection , data clustering and multivariate data visualization etc . Accurate identification of outliers plays an important role in statistical analysis. If classical statistical models are blindly applied to data containing outliers, the results can be ...

Gaussian data is pervasive and many learning algorithms (e.g., k-means) model their inputs as a single sample drawn from a multivariate Gaussian. However, in many real-life settings, each input object is best described by multiple samples drawn from a multivariate Gaussian. Such data can arise, for example, in a movie review database where each movie is rated by several users, or in time-series...

The authors present an application of multivariate non-hierarchical statistical clustering to geographic environmental data from the 48 conterminous United States in order to produce maps of regions of ecological similarity called ecore-gions. Nine input variables thought to aaect the growth of vegetation are clustered at a resolution of one square kilometer. These data represent over 7.8 milli...

In this paper, we study an unsupervised clustering problem. The originality of this problem lies in the data, which consist of the positions of five separate X-ray beams on a circle. Radiation therapists positioned the five X-ray beam 'projectors' around each patient on a predefined circle. However, similarities exist in positioning for certain groups of patients, and we aim to describe these s...

sets as the basis for visualizing ecoregion maps.1,2 Ecoregions are areas containing similar environmental conditions that are classified for particular purposes. For example, the US Department of Agriculture publishes a map of Plant Hardiness Zones, which divides the US into different ecoregions so that gardeners can select appropriate plants and shrubs for their particular area. The ecoregion...

Multivariate time series (MTS) data are ubiquitous in science and daily life, and how to measure their similarity is a core part of MTS analyzing process. Many of the research efforts in this context have focused on proposing novel similarity measures for the underlying data. However, with the countless techniques to estimate similarity between MTS, this field suffers from a lack of comparative...

The forward search provides a series of robust parameter estimates based on increasing numbers of observations. The resulting series of robustMahalanobis distances is used to clustermultivariate normal data.Themethod depends on envelopes of the distribution of the test statistics in forward plots.These envelopes can be found by simulation; flexible polynomial approximations to the envelopes are...

A data stream is a flow of data produced continuously along the time. Storing and analyzing such information become challenging due to exponential growth of the data volume collected. In this context, some methods were proposed to cluster data streams with similar behavior along the time. However, those methods have failed on clustering data flows with more than one attribute, i.e., multivariat...