Principal components or empirical orthogonal functions are virtually the sole statistical tool used to date for investigations of space-time variability of meteorological elements. Maximum statistical efficiency and possible physical interpretation of empirical orthogonal functions derives from the assumptions of stationarity and homoscedasticity of the scalar variables in space and time. In th...

Principal component analysis (PCA) and independent component analysis (ICA) were examined in their ability to recover dipole sources from simulated data. Datasets of EEG segments were generated that contained cortical sources that were temporally overlapping or non-overlapping, and dipole sources with varying degree of spatial orthogonality. For temporal overlapping sources, both PCA and ICA re...

This work proposes an extension of the functional principal components analysis, or Karhunen-Loève expansion, which can take into account non-parametrically the effects of an additional covariate. Such models can also be interpreted as non-parametric mixed effects models for functional data. We propose estimators based on kernel smoothers and a data-driven selection procedure of the smoothing p...

Traditional bidirectional two-dimension (2D) principal component analysis ((2D)PCA-L2) is sensitive to outliers because its objective function is the least squares criterion based on L2-norm. This paper proposes a simple but effective L1-norm-based bidirectional 2D principal component analysis ((2D)PCA-L1), which jointly takes advantage of the merits of bidirectional 2D subspace learning and L1...

The aim of this paper is to simultaneously estimate n curves corrupted by noise, this means several observations of a random process. The non parametric estimation of the sampled paths leads to a new kind of functional principal components analysis which simultaneously takes into account a dimensionality and a smoothness constraint. Furthermore, the use of B-spline approximation to estimate the...

in this article the methodology proposed by li and wang for mixed qualitative and quantitative modeling and simulation of temporal behavior of processing unit is reexamined and extended to more complex case. the main issue of their approach considers the multivariate statistics of principal component analysis (pca), along with clustered fuzzy digraphs and reasoning. the pca and fuzzy clustering...

this study aims to assess the effect of grazing intensity on vegetation structure, soil nutrient concentrations and soil physical properties. the study was carried out in steppe rangelands of saveh, markazi province, iran. four sites with four grazing intensities including very high, high, moderate and non-grazed with the same ecological conditions were selected. to study various vegetation and...

Cornelian cherry (Cornus mas L.), considered as the ancestor of cultivated trees in Arasbaran region, is a medicinally and economically plant species. However, little is known about genetic diversity, breeding programs, and population structure of this species in mentioned region. Keeping this in view, the main objectives of present study were to analysis the genetic diversity, phyloge...

there is little chance for species with competitor to develop intraspecific variability such as sexual dimorphism. sitta tephronota is a well-known rock-dwelling bird species in iran, which occurs in zagros mountains in strong ecological competition with sitta neumayer. thus, no sexual dimorphism is expected for sitta tephronota in this area. despite the role of this species in the rise of the ...