Perturbation, extraction and refinement of invariant pairs for matrix polynomials

Generalizing the notion of an eigenvector, invariant subspaces are frequently used in the context of linear eigenvalue problems, leading to conceptually elegant and numerically stable formulations in applications that require the computation of several eigenvalues and/or eigenvectors. Similar benefits can be expected for polynomial eigenvalue problems, for which the concept of an invariant subspace needs to be replaced by the concept of an invariant pair. Little has been known so far about numerical aspects of such invariant pairs. The aim of this paper is to fill this gap. The behavior of invariant pairs under perturbations of the matrix polynomial is studied and a first-order perturbation expansion is given. From a computational point of view, we investigate how to best extract invariant pairs from a linearization of the matrix polynomial. Moreover, we describe efficient refinement procedures directly based on the polynomial formulation. Numerical experiments with matrix polynomials from a number of applications demonstrate the effectiveness of our extraction and refinement procedures.

A linear CDMA detector based on minimum variance distortionless response (MVDR)

A bit-level processing (BLP) based linear CDMA detector is derived following the principle of minimum variance distortionless response (MVDR). The combining taps for the MVDR detector are determined from (1) the covariance matrix of the matched filter output, and (2) the corresponding row (or column) of the user correlation matrix. Due to the interference suppression capability of MVDR and the fact that no inversion of the user correlation matrix is involved, the influence of the synchronisation errors is greatly reduced. The detector performance is demonstrated via computer simulations (both synchronisation errors and intercell interference are considered).

Random orthogonal matrix simulation

This paper introduces a method for simulating multivariate samples that have exact means, covariances, skewness and kurtosis. We introduce a new class of rectangular orthogonal matrix which is fundamental to the methodology and we call these matrices L matrices. They may be deterministic, parametric or data specific in nature. The target moments determine the L matrix then infinitely many random samples with the same exact moments may be generated by multiplying the L matrix by arbitrary random orthogonal matrices. This methodology is thus termed “ROM simulation”. Considering certain elementary types of random orthogonal matrices we demonstrate that they generate samples with different characteristics. ROM simulation has applications to many problems that are resolved using standard Monte Carlo methods. But no parametric assumptions are required (unless parametric L matrices are used) so there is no sampling error caused by the discrete approximation of a continuous distribution, which is a major source of error in standard Monte Carlo simulations. For illustration, we apply ROM simulation to determine the value-at-risk of a stock portfolio.

Robust pole assignment in linear state feedback

Numerical methods are described for determining robust, or well-conditioned, solutions to the problem of pole assignment by state feedback. The solutions obtained are such that the sensitivity of the assigned poles to perturbations in the system and gain matrices is minimized. It is shown that for these solutions, upper bounds on the norm of the feedback matrix and on the transient response are also minimized and a lower bound on the stability margin is maximized. A measure is derived which indicates the optimal conditioning that may be expected for a particular system with a given set of closed-loop poles, and hence the suitability of the given poles for assignment.

Robust eigenstructure assignment in quadratic matrix polynomials: nonsingular case

Feedback design for a second-order control system leads to an eigenstructure assignment problem for a quadratic matrix polynomial. It is desirable that the feedback controller not only assigns specified eigenvalues to the second-order closed loop system but also that the system is robust, or insensitive to perturbations. We derive here new sensitivity measures, or condition numbers, for the eigenvalues of the quadratic matrix polynomial and define a measure of the robustness of the corresponding system. We then show that the robustness of the quadratic inverse eigenvalue problem can be achieved by solving a generalized linear eigenvalue assignment problem subject to structured perturbations. Numerically reliable methods for solving the structured generalized linear problem are developed that take advantage of the special properties of the system in order to minimize the computational work required. In this part of the work we treat the case where the leading coefficient matrix in the quadratic polynomial is nonsingular, which ensures that the polynomial is regular. In a second part, we will examine the case where the open loop matrix polynomial is not necessarily regular.

On the Convergence of Two-Stage Iterative Processes for Solving Linear Equations

This paper considers two-stage iterative processes for solving the linear system $Af = b$. The outer iteration is defined by $Mf^{k + 1} = Nf^k + b$, where $M$ is a nonsingular matrix such that $M - N = A$. At each stage $f^{k + 1} $ is computed approximately using an inner iteration process to solve $Mv = Nf^k + b$ for $v$. At the $k$th outer iteration, $p_k $ inner iterations are performed. It is shown that this procedure converges if $p_k \geqq P$ for some $P$ provided that the inner iteration is convergent and that the outer process would converge if $f^{k + 1} $ were determined exactly at every step. Convergence is also proved under more specialized conditions, and for the procedure where $p_k = p$ for all $k$, an estimate for $p$ is obtained which optimizes the convergence rate. Examples are given for systems arising from the numerical solution of elliptic partial differential equations and numerical results are presented.

The compositional and configurational heterogeneity of matrix habitats shape woodland carabid communities in wooded-agricultural landscapes

Landscape heterogeneity (the composition and configuration of matrix habitats) plays a major role in shaping species communities in wooded-agricultural landscapes. However, few studies consider the influence of different types of semi-natural and linear habitats in the matrix, despite their known ecological value for biodiversity. Objective To investigate the importance of the composition and configuration of matrix habitats for woodland carabid communities and identify whether specific landscape features can help to maintain long-term populations in wooded-agricultural environments. Methods Carabids were sampled from woodlands in 36 tetrads of 4 km2 across southern Britain. Landscape heterogeneity including an innovative representation of linear habitats was quantified for each tetrad. Carabid community response was analysed using ordination methods combined with variation partitioning and additional response trait analyses. Results Woodland carabid community response was trait-specific and better explained by simultaneously considering the composition and configuration of matrix habitats. Semi-natural and linear features provided significant refuge habitat and functional connectivity. Mature hedgerows were essential for slow-dispersing carabids in fragmented landscapes. Species commonly associated with heathland were correlated with inland water and woodland patches despite widespread heathland conversion to agricultural land, suggesting that species may persist for some decades when elements representative of the original habitat are retained following landscape modification. Conclusions Semi-natural and linear habitats have high biodiversity value. Landowners should identify features that can provide additional resources or functional connectivity for species relative to other habitat types in the landscape matrix. Agri-environment options should consider landscape heterogeneity to identify the most efficacious changes for biodiversity.

Acellular dermal matrix as a barrier in guided bone regeneration: a clinical, radiographic and histomorphometric study in dogs

Objectives The purpose of this study was to evaluate the effectiveness of the acellular dermal matrix (ADM) as a membrane for guided bone regeneration (GBR), in comparison with a bioabsorbable membrane. Material and methods In seven dogs, the mandibular pre-molars were extracted. After 8 weeks, one bone defect was surgically created bilaterally and the GBR was performed. Each side was randomly assigned to the control group (CG: bioabsorbable membrane made of glycolide and lactide copolymer) or the test group (TG: ADM as a membrane). Immediately following GBR, standardized digital X-ray radiographs were taken, and were repeated at 8 and 16 weeks post-operatively. Before the GBR and euthanasia, clinical measurements of the width and thickness of the keratinized tissue (WKT and TKT, respectively) were performed. One animal was excluded from the study due to complications in the TG during wound healing; therefore, six dogs remained in the sample. The dogs were sacrificed 16 weeks following GBR, and a histomorphometric analysis was performed. Area measurements of new tissue and new bone, and linear measurements of bone height were performed. Results Post-operative healing of the CG was uneventful. In the TG membrane was exposed in two animals, and one of them was excluded from the sample. There were no statistically significant differences between the groups for any histomorphometric measurement. Clinically, both groups showed an increase in the TKT and a reduction in the WKT. Radiographically, an image suggestive of new bone formation could be observed in both groups at 8 and 16 weeks following GBR. Conclusion ADM acted as a barrier in GBR, with clinical, radiographic and histomorphometric results similar to those obtained with the bioabsorbable membrane. To cite this article:Borges GJ, Novaes AB Jr, de Moraes Grisi MF, Palioto DB, Taba M Jr, de Souza SLS. Acellular dermal matrix as a barrier in guided bone regeneration: a clinical, radiographic and histomorphometric study in dogs.Clin. Oral Impl. Res. 20, 2009; 1105-1115.

On S-matrix factorization of the Landau-Lifshitz model

We consider the three-particle scattering S-matrix for the Landau-Lifshitz model by directly computing the set of the Feynman diagrams up to the second order. We show, following the analogous computations for the non-linear Schrdinger model [1, 2], that the three-particle S-matrix is factorizable in the first non-trivial order.

Hyperfine and magnetic properties of Fe-Cu clusters and Fe precipitates embedded in a Cu matrix

Using the first-principles real-space linear muffin-tin orbital method within the atomic sphere approximation (RS-LMTO-ASA) we study hyperfine and local magnetic properties of substituted pure Fe and Fe-Cu clusters in an fcc Cu matrix. Spin and orbital contributions to magnetic moments, hyperfine fields and the Mossbauer isomer shifts at the Fe sites in Fe precipitates and Fe-Cu alloy clusters of sizes up to 60 Fe atoms embedded in the Cu matrix are calculated and the influence of the local environment on these properties is discussed.

Leverage analysis for linear mixed models

We consider a generalized leverage matrix useful for the identification of influential units and observations in linear mixed models and show how a decomposition of this matrix may be employed to identify high leverage points for both the marginal fitted values and the random effect component of the conditional fitted values. We illustrate the different uses of the two components of the decomposition with a simulated example as well as with a real data set.

Improved testing inference in mixed linear models

Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Often, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test, and also to a test obtained from a modified profile likelihood function. Our results generalize those in [Zucker, D.M., Lieberman, O., Manor, O., 2000. Improved small sample inference in the mixed linear model: Bartlett correction and adjusted likelihood. Journal of the Royal Statistical Society B, 62,827-838] by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report simulation results which show that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presented and discussed. (C) 2008 Elsevier B.V. All rights reserved.

Covariance matrix formula for Birnbaum-Saunders regression models

The Birnbaum-Saunders regression model is commonly used in reliability studies. We derive a simple matrix formula for second-order covariances of maximum-likelihood estimators in this class of models. The formula is quite suitable for computer implementation, since it involves only simple operations on matrices and vectors. Some simulation results show that the second-order covariances can be quite pronounced in small to moderate sample sizes. We also present empirical applications.

Análise não linear física e geométrica de pórticos espaciais

Apresenta-se uma formulação do tipo incrementaliterativa destinada a análise não linear de pórticos espaciais. Considera-se os efeitos não lineares introduzidos pelas mudanças de configuração geométrica da estrutura e também pela combinação destes efeitos com aqueles inerentes ao comportamento plástico exibido pelo material. As relações cinemáticas empregadas permitem a consideração de deslocamentos arbitrariamente grandes, acompanhadas de pequenas deformações . A modelagem do comportamento plástico do material é efetuada através do conceito de rótula plástica, estabelecido a partir de um critério de plastificação generalizado. Adota-se uma matriz de rigidez geométrica de barra baseada em momentos semitangenciais. Para elementos com extremos plastificados, é deduzida uma matriz de rigidez elasto-plástica. Emprega-se um método numérico do tipo incremental-iterativo, que utiliza como condição básica de controle da análise a constância do trabalho realizado pelos incrementos de cargas, em cada passo incremental (Método de Controle por Trabalho).A formulação permite uma descricão completa do desempenho mecânico da estrutura, inclusive em estágio de deformação pós-crítico em que ocorre regressão do carregamento com aumento de deslocamentos, ou vice-versa. A formulação foi implementada em um programa computacional elaborado em linguagem FORTRAN. Vários exemplos numéricos são apresentados para mostrar a eficiência das procedimentos propostos.

A class of improved heteroskedasticity-consistent covariance matrix estimators

The heteroskedasticity-consistent covariance matrix estimator proposed by White (1980), also known as HC0, is commonly used in practical applications and is implemented into a number of statistical software. Cribari–Neto, Ferrari & Cordeiro (2000) have developed a bias-adjustment scheme that delivers bias-corrected White estimators. There are several variants of the original White estimator that also commonly used by practitioners. These include the HC1, HC2 and HC3 estimators, which have proven to have superior small-sample behavior relative to White’s estimator. This paper defines a general bias-correction mechamism that can be applied not only to White’s estimator, but to variants of this estimator as well, such as HC1, HC2 and HC3. Numerical evidence on the usefulness of the proposed corrections is also presented. Overall, the results favor the sequence of improved HC2 estimators.