Search results for "principal"
showing 10 items of 795 documents
smatr 3 - an R package for estimation and inference about allometric lines
2011
Summary 1. The Standardised Major Axis Tests and Routines (SMATR) software provides tools for estimation and inference about allometric lines, currently widely used in ecology and evolution. 2. This paper describes some significant improvements to the functionality of the package, now available on R in smatr version 3. 3. New inclusions in the package include sma and ma functions that accept formula input and perform the key inference tasks; multiple comparisons; graphical methods for visualising data and checking (S)MA assumptions; robust (S)MA estimation and inference tools.
Finland: Finnish Principal
2016
The presentation of principalship in Finland begins by giving an overall description of the Finnish education system and of the formal position of principals in Finland. The more detailed examination of the Finnish principal comprises two main sources. Both sources are reviews on research on principals in Finland in 2000–2010. The first one was conducted for the Swedish Research Council by Risku and Kanervio (Doctoral and regular research on principals in Finland 2000–2010. In: Johansson O (ed) Rektor – en forskningsoversikt 2000–2010 [Principal – a research report]. Vetenskapsradets rapportserie 4:161–186, 2011). The second one is a report by Alava et al. (Changing school management. Statu…
Critical Fracture Plane Under Multiaxial Random Loading by Means of Euler Angles Averaging
1999
ABSTRACT Several authors have experimentally observed that the position of the fatigue fracture plane strongly depends on the directions of the principal stresses or strains. The expected principal stress directions under multiaxial random loading are obtained herein by averaging the instantaneous values of the three Euler angles through some suitable weight functions, in order to take into account the main factors influencing the fatigue fracture behaviour. Then the correlation between such theoretical principal directions and the experimental fracture plane is examined for some biaxial random fatigue tests.
Phylogeography of a Habitat Specialist with High Dispersal Capability: The Savi’s Warbler Locustella luscinioides
2012
In order to describe the influence of Pleistocene glaciations on the genetic structure and demography of a highly mobile, but specialized, passerine, the Savi's Warbler (Locustella luscinioides), mitochondrial DNA sequences (ND2) and microsatellites were analysed in c.330 individuals of 17 breeding and two wintering populations. Phylogenetic, population genetics and coalescent methods were used to describe the genetic structure, determine the timing of the major splits and model the demography of populations. Savi's Warblers split from its sister species c.8 million years ago and have two major haplotype groups that diverged in the early/middle Pleistocene. One of these clades originated in…
G-Spaces and Kaluza-Klein Theory
1988
G-spaces are present whenever symmetries are relevant in physics. After a short introduction to this subject, spontaneous symmetry breaking in elementary particle physics is considered from this point of view. Kaluza-Klein theory is discussed in a purely geometrical formulation. Some results in connection with the geometrical compactification scheme are presented.
Nonlinearities and Adaptation of Color Vision from Sequential Principal Curves Analysis
2016
Mechanisms of human color vision are characterized by two phenomenological aspects: the system is nonlinear and adaptive to changing environments. Conventional attempts to derive these features from statistics use separate arguments for each aspect. The few statistical explanations that do consider both phenomena simultaneously follow parametric formulations based on empirical models. Therefore, it may be argued that the behavior does not come directly from the color statistics but from the convenient functional form adopted. In addition, many times the whole statistical analysis is based on simplified databases that disregard relevant physical effects in the input signal, as, for instance…
Optimized Kernel Entropy Components
2016
This work addresses two main issues of the standard Kernel Entropy Component Analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of by variance as in Kernel Principal Components Analysis. In this work, we propose an extension of the KECA method, named Optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular…
PRINCIPAL POLYNOMIAL ANALYSIS
2014
© 2014 World Scientific Publishing Company. This paper presents a new framework for manifold learning based on a sequence of principal polynomials that capture the possibly nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) generalizes PCA by modeling the directions of maximal variance by means of curves instead of straight lines. Contrarily to previous approaches PPA reduces to performing simple univariate regressions which makes it computationally feasible and robust. Moreover PPA shows a number of interesting analytical properties. First PPA is a volume preserving map which in turn guarantees the existence of the inverse. Second such an inverse can be obtained…
Conditional Bias Robust Estimation of the Total of Curve Data by Sampling in a Finite Population: An Illustration on Electricity Load Curves
2020
Abstract For marketing or power grid management purposes, many studies based on the analysis of total electricity consumption curves of groups of customers are now carried out by electricity companies. Aggregated totals or mean load curves are estimated using individual curves measured at fine time grid and collected according to some sampling design. Due to the skewness of the distribution of electricity consumptions, these samples often contain outlying curves which may have an important impact on the usual estimation procedures. We introduce several robust estimators of the total consumption curve which are not sensitive to such outlying curves. These estimators are based on the conditio…
Asymptotic and bootstrap tests for subspace dimension
2022
Most linear dimension reduction methods proposed in the literature can be formulated using an appropriate pair of scatter matrices, see e.g. Ye and Weiss (2003), Tyler et al. (2009), Bura and Yang (2011), Liski et al. (2014) and Luo and Li (2016). The eigen-decomposition of one scatter matrix with respect to another is then often used to determine the dimension of the signal subspace and to separate signal and noise parts of the data. Three popular dimension reduction methods, namely principal component analysis (PCA), fourth order blind identification (FOBI) and sliced inverse regression (SIR) are considered in detail and the first two moments of subsets of the eigenvalues are used to test…