Exponential separation and principal Lyapunov exponent/spectrum for random/nonautonomous parabolic equations

The purpose of the paper is to extend the principal eigenvalue and principal eigenfunction theory for time independent and periodic parabolic equations to random and general nonautonomous ones. In the random case, a notion of principal Lyapunov exponent serving as an analog of principal eigenvalue is introduced. It is shown that the principal Lyapunov exponent is deterministic and of simple multiplicity. It is also shown that there is a one-dimensional invariant random subbundle corresponding to the solutions that are globally defined and of the same sign, which serves as an analog of principal eigenfunction. In addition, monotonicity of the principal Lyapunov exponent with respect to the zero-order terms both in the equation and in the boundary condition is proved. When the second- and first-order terms are deterministic, it is proved that the principal Lyapunov exponent is greater than or equal to the principal eigenvalue of the associated time-averaged equation. In the general nonautonomous case, the concepts of principal spectrum, which serves as an analog of principal eigenvalue, and principal Lyapunov exponents are introduced. As is known, the principal spectrum is a compact interval. It is proved in the paper that the principal spectrum contains all the principal Lyapunov exponents. When the second and first-order terms are time independent, a lower estimate of the infimum of the principal spectrum is given in terms of an associated time-averaged equation.     

Principal component histograms from interval-valued observations

The focus of this paper is to propose an approach to construct histogram values for the principal components of interval-valued observations. Le-Rademacher and Billard (J Comput Graph Stat 21:413–432, 2012) show that for a principal component analysis on interval-valued observations, the resulting observations in principal component space are polytopes formed by the convex hulls of linearly transformed vertices of the observed hyper-rectangles. In this paper, we propose an algorithm to translate these polytopes into histogram-valued data to provide numerical values for the principal components to be used as input in further analysis. Other existing methods of principal component analysis for interval-valued data construct the principal components, themselves, as intervals which implicitly assume that all values within an observation are uniformly distributed along the principal components axes. However, this assumption is only true in special cases where the variables in the dataset are mutually uncorrelated. Representation of the principal components as histogram values proposed herein more accurately reflects the variation in the internal structure of the observations in a principal component space. As a consequence, subsequent analyses using histogram-valued principal components as input result in improved accuracy.     

Compact Topological Inverse Semigroups

A locally compact commutative band with open principal ideals is a zero-dimensional scattered space. Cardinal invariants of locally compact and compact commutative bands with open principal ideals is investigated. A base of the topology of a compact commutative band with open principal ideals is determined and the structure of such compact semilattices in which every principal lower set is a chain is described. Every first countable compact inverse semigroup with open right (left, two-sided) principal ideals is metrizable     

考虑主应力轴旋转的土体本构关系研究进展

对目前国内外考虑主应力轴旋转的试验研究及本构模型研究进行了总结分析,并对进一步研究提出了相应的建议．基于不同的加载条件,从纯主应力轴旋转和耦合主应力轴旋转两个方面,较全面的描述了主应力轴旋转情况下土体的基本变形特性,并对考虑主应力轴旋转的土体变形试验提出了进一步研究的建议．较为系统地评述了当前较有代表性的考虑主应力轴旋转的土体本构模型（边界面模型、多机构模型、运动硬化模型和广义塑性模型）,得出了广义塑性模型更适合用来描述考虑主应力轴旋转的土体变形特性的结论．总结未来考虑主应力轴旋转的土体本构关系研究的主要方向是:把握主应力轴旋转情况下土体变形的本质特性,建立推理严密、形式简单、适用方便的本构模型,并用来指导工程实践．     

基于主成分分析法的综合评价方法的改进

针对用主成分分析法做综合评价存在的问题,提出了改进的方法即当第一主成分的综合评价值和熵值法得到的综合评价值具有一致性时,将两种评价结果进行集成综合评价,若两种评价结果不具有一致性时则采用主成分聚类法进行综合评价.     

基于主成分分析的水质评价方法

主成分分析法能够在保证原始数据信息损失最小的情况下,以少数的综合变量取代原有的多维变量,使数据结构大为简化,并且客观地确定变量权数,避免了主观随意性.应用主成分分析法对长春市地面水环境进行评价,且与其它评价方法相比较,结果显示主成分分析法更客观且指导性较强,是一种行之有效的水质评价方法.通过主成分分析进行水质评价,可为水资源规划、利用、开发和环境系统优化提供更为客观的参考依据.     

Identifiability of causal effects on a binary outcome within principal strata

Principal strata are defined by the potential values of a post-treatment variable, and a principal effect is a causal effect within a principal stratum. Identifying the principal effect within every principal stratum is quite challenging. In this paper, we propose an approach for identifying principal effects on a binary outcome via a pre-treatment covariate. We prove the identifiability with single post-treatment intervention under the monotonicity assumption. Furthermore, we discuss the local identifiability with multicomponent intervention. Simulations are performed to evaluate our approach. We also apply it to a real data set from the Improving Mood-Promoting Access to Collaborate Treatment program.     

Parallel Principal Axes

Parallel principal axes are introduced and used to investigate the structure of multivariate distributions. In the class of elliptical distributions, it is shown that self-consistency of parallel principal axes characterizes normality. Parallel principal axes are used to illustrate the equivalent event fallacy in the context of self-consistency. Finally, the idea of piecewise principal component axes is introduced and related to an allometric extension model.     

Principal differential analysis of the Aneurisk65 data set

We explore the use of principal differential analysis as a tool for performing dimensional reduction of functional data sets. In particular, we compare the results provided by principal differential analysis and by functional principal component analysis in the dimensional reduction of three synthetic data sets, and of a real data set concerning 65 three-dimensional cerebral geometries, the AneuRisk65 data set. The analyses show that principal differential analysis can provide an alternative and effective representation of functional data, easily interpretable in terms of exponential, sinusoidal, or damped-sinusoidal functions and providing a different insight to the functional data set under investigation. Moreover, in the analysis of the AneuRisk65 data set, principal differential analysis is able to detect interesting features of the data, such as the rippling effect of the vessel surface, that functional principal component analysis is not able to detect.     

主转动角与主转动轴的显式表示

本文利用Cayley-Hamilton定理,给出了两种直接获得转动张量显式表示的方法。一种为只含变形梯度较低次幂的表达形式,利用此表示,获得了主转动角的计算公式和主转动轴的显式表示。而另一种则是不含复杂系数且含变量个数较少的高效获得转动张量的方法。进一步,给出了主转动角和主转动轴的一些性质。     

On the asymptotic behavior of general projection-pursuit estimators under the common principal components model

The common principal components model for several groups of multivariate observations assumes equal principal axes among the groups. Robust estimators can be defined replacing the sample variance by a robust dispersion measure. This paper studies the asymptotic distribution of robust projection-pursuit estimators under a common principal components model.     

ISOPARAMETRIC HYPERSURFACES IN CP~n WITH CONSTANT PRINCIPAL CURVATURES

This paper proves that the number of distinct principal curvatures of a realisoparametric hypersurface in CP~n with constant principal curvatures can be only 2, 3 or 5.The prehnage of such hypersurface under the Hopf fibration is an isoparametrichypersarface in S~(2n+l) with 2 or 4 distinct principal curvatures. For real isoparametrichypersurfaces in CP~n with 5 distinct constant principal curvatures a local structuretheorem is given.     

Congruence computations in principal arithmetical varieties

This paper is a continuation of the earlier paper by the same authors in which a primary result was that every arithmetical affine complete variety of finite type is a principal arithmetical variety with respect to an appropriately chosen Pixley term. The paper begins by presenting an extension of this result to all finitely generated congruences and, as an example, constructs a closed form solution formula for any finitely presented system of pairwise compatible congruences (the Chinese remainder theorem). It is also shown that in all such varieties the meet of principal congruences is also principal, and finally, if a minimal generating algebra of the variety is regular, it is shown that the variety is also regular and the join of principal congruences is again principal.     

高维稳健主成分聚类方法及其应用研究

随着信息技术的高速发展,每条数据所包含的信息越来越丰富,使得数据不可避免地含有异常值,且随着维数的增加,异常值出现的可能性更大。传统的主成分聚类分析对异常值特別敏感,基于MCD估计的主成分聚类方法虽然对异常值具有防御作用,但是在高维数据下MCD估计的偏差过大,其稳健性显著降低,而且当维数大于观测值个数时MCD估计失效。为此本文提出了基于MRCD估计的稳健主成分聚类方法,数值模拟和实证分析表明,基于MRCD估计的主成分聚类分析的效果优于传统的主成分聚类分析和基于MCD估计的主成分聚类分析,尤其是在维数大于样本观测值的情况下,MRCD估计更为有效。     

主分量回归在骨龄系数测定中的应用

运用主成分分析法提取了十二种足骨发育等级的主分量,接着进行主分量回归,然后再进行分年龄段回归,可得用于年龄鉴定的骨龄系数表。     

Equivariant class group. II. Enriched descent theorem

We prove a version of Grothendieck’s descent theorem on an ‘enriched’ principal fiber bundle, a principal fiber bundle with an action of a larger group scheme. Using this, we prove the isomorphisms of the equivariant Picard and the class groups arising from such a principal fiber bundle.     

VonMises分布表的一种插值方法

本文给出ＶｏｎＭｉｓｅｓ分布表的一种插值方法     

对应用主成分法进行综合评价的探讨

本文针对用主成分法进行综合评价时存在的缺点,提出了分组主成分评价法。即先用因子分析法对变量进行分组后,然后再分别对各组变量进行主成分评价,既保证了主成分法的优点,也克服它在评价中的缺点,提高综合评价结果的合理性。并用该方法对实例进行了分析,取得了较好的效果。     

Semistable and numerically effective principal (Higgs) bundles

We study Miyaoka-type semistability criteria for principal Higgs G-bundles E on complex projective manifolds of any dimension. We prove that E has the property of being semistable after pullback to any projective curve if and only if certain line bundles, obtained from some characters of the parabolic subgroups of G, are numerically effective. One also proves that these conditions are met for semistable principal Higgs bundles whose adjoint bundle has vanishing second Chern class.In a second part of the paper, we introduce notions of numerical effectiveness and numerical flatness for principal (Higgs) bundles, discussing their main properties. For (non-Higgs) principal bundles, we show that a numerically flat principal bundle admits a reduction to a Levi factor which has a flat Hermitian–Yang–Mills connection, and, as a consequence, that the cohomology ring of a numerically flat principal bundle with coefficients in R is trivial. To our knowledge this notion of numerical effectiveness is new even in the case of (non-Higgs) principal bundles.