Seemingly unrelated linear regression for contaminated data based on Gaussian mixtures

In this thesis, new classes of models for multivariate linear regression defined by finite mixtures of seemingly unrelated contaminated normal regression models and seemingly unrelated contaminated normal cluster-weighted models are illustrated. The main difference between such families is that the covariates are treated as fixed in the former class of models and as random in the latter. Thus, in cluster-weighted models the assignment of the data points to the unknown groups of observations depends also by the covariates. These classes provide an extension to mixture-based regression analysis for modelling multivariate and correlated responses in the presence of mild outliers that allows to specify a different vector of regressors for the prediction of each response. Expectation-conditional maximisation algorithms for the calculation of the maximum likelihood estimate of the model parameters have been derived. As the number of free parameters incresases quadratically with the number of responses and the covariates, analyses based on the proposed models can become unfeasible in practical applications. These problems have been overcome by introducing constraints on the elements of the covariance matrices according to an approach based on the eigen-decomposition of the covariance matrices. The performances of the new models have been studied by simulations and using real datasets in comparison with other models. In order to gain additional flexibility, mixtures of seemingly unrelated contaminated normal regressions models have also been specified so as to allow mixing proportions to be expressed as functions of concomitant covariates. An illustration of the new models with concomitant variables and a study on housing tension in the municipalities of the Emilia-Romagna region based on different types of multivariate linear regression models have been performed.

Multifractality in the random parameter model for multivariate time series

The Random Parameter model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we explore the scaling properties of the model, as observed in the multifractal structure of the simulated time series. We use the Wavelet Transform Modulus Maxima technique to obtain the multifractal spectrum dependence with the parameters of the model. The model shows a scaling structure compatible with the stylized facts for a reasonable choice of the parameter values. (C) 2009 Elsevier B.V. All rights reserved.

On the heritability of inspection time and its covariance with IQ: A twin study

Using the classical twin design, this study investigates the influence of genetic factors on the large phenotypic variance in inspection time (IT), and whether the well established IT-IQ association can be explained by a common genetic factor. Three hundred ninety pairs of twins (184 monozygotic, MZ; 206 dizygotic, DZ) with a mean age of 16 years participated, and 49 pairs returned approximately 3 months, later for retesting. As in many IT studies, the pi figure stimulus was used and IT was estimated from the cumulative normal ogive. IT ranged from 39.4 to 774.1 ms (159 +/- 110.1 ms) with faster ITs (by an average of 26.9 ms) found in the retest session from which a reliability of .69 was estimated. Full-scale IQ (FIQ) was assessed by the Multidimensional Aptitude Battery (MAB) and ranged from 79 to 145 (111 +/- 13). The phenotypic association between IT and FIQ was confirmed (- .35) and bivariate results showed that a common genetic factor accounted for 36% of the variance in IT and 32% of the variance in FIQ. The maximum likelihood estimate of the genetic correlation was - .63. When performance and verbal IQ (PIQ & VIQ) were analysed with IT, a stronger phenotypic and genetic relationship was found between PIQ and IT than with VIQ. A large part of the IT variance (64%) was accounted for by a unique environmental factor. Further genetic factors were needed to explain the remaining variance in IQ with a small component of unique environmental variance present. The separability of a shared genetic factor influencing IT and IQ from the total genetic variance in IQ suggests that IT affects a specific subcomponent of intelligence rather than a generalised efficiency. (C) 2001 Elsevier Science Inc. All rights reserved.

A comparative study of energy transfer in dye mixtures in monomer and polymer matrices under pulsed laser excitation

This study was conducted to identify the concentration dependence of the operating wavelengths and the relative intensities in which a dye mixture doped polymer optical fibre can operate. A comparative study of the radiative and Forster type energy transfer processes in Coumarin 540:Rhodamine 6G, Coumarin 540:Rhodamine B and Rhodamine 6G:Rhodamine B in methyl methacrylate (MMA) and poly(methyl methacrylate) (PMMA) was done by fabricating a series of dye mixture doped polymer rods which have two emission peaks with varying relative intensities. These rods can be used as preforms for the fabrication of polymer optical fibre amplifiers operating in the multi-wavelength regime. The 445 nm line from an Nd:YAG pumped optical parametric oscillator (OPO) was used as the excitation source for the first two dye pairs and a frequency doubled Nd:YAG laser emitting at 532 nm was used to excite the Rh 6G:Rh B pair. The fluorescence lifetimes of the donor molecule in pure form as well as in the mixtures were experimentally measured in both monomer and polymer matrices by time-correlated single photon counting technique. The energy transfer rate constants and transfer efficiencies were calculated and their dependence on the acceptor concentration was analysed. It was found that radiative energy transfer mechanisms are more efficient in all the three dye pairs in liquid and solid matrices.

Multivariate analyses of variance and covariance for simulation studies involving normal time series

Photocopy.

The effects of varying time under tension and volume load on acute neuromuscular responses

The purpose of this study was to examine the effects of different methods of measuring training volume, controlled in different ways, on selected variables that reflect acute neuromuscular responses. Eighteen resistance-trained males performed three fatiguing protocols of dynamic constant external resistance exercise, involving elbow flexors, that manipulated either time-under-tension (TUT) or volume load (VL), defined as the product of training load and repetitions. Protocol A provided a standard for TUT and VL. Protocol B involved the same VL as Protocol A but only 40% concentric TUT; Protocol C was equated to Protocol A for TUT but only involved 50% VL. Fatigue was assessed by changes in maximum voluntary isometric contraction (MVIC), interpolated doublet (ID), muscle twitch characteristics (peak twitch, time to peak twitch, 0.5 relaxation time, and mean rates of force development and twitch relaxation). All protocols produced significant changes (P

Discrete Time Bisexual Branching Processes in Varying Environments

2000 Mathematics Subject Classification: 60J80

A Metabolomic Protocol For Plant Systematics By Matrix-assisted Laser-desorption/ionization Time-of Flight Mass Spectrometry.

Matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS) has been widely used for the identification and classification of microorganisms based on their proteomic fingerprints. However, the use of MALDI-TOF MS in plant research has been very limited. In the present study, a first protocol is proposed for metabolic fingerprinting by MALDI-TOF MS using three different MALDI matrices with subsequent multivariate data analysis by in-house algorithms implemented in the R environment for the taxonomic classification of plants from different genera, families and orders. By merging the data acquired with different matrices, different ionization modes and using careful algorithms and parameter selection, we demonstrate that a close taxonomic classification can be achieved based on plant metabolic fingerprints, with 92% similarity to the taxonomic classifications found in literature. The present work therefore highlights the great potential of applying MALDI-TOF MS for the taxonomic classification of plants and, furthermore, provides a preliminary foundation for future research.

Porcine skin as a source of biodegradable matrices: alkaline treatment and glutaraldehyde crosslinking

In this work, the modifications promoted by alkaline hydrolysis and glutaraldehyde (GA) crosslinking on type I collagen found in porcine skin have been studied. Collagen matrices were obtained from the alkaline hydrolysis of porcine skin, with subsequent GA crosslinking in different concentrations and reaction times. The elastin content determination showed that independent of the treatment, elastin was present in the matrices. Results obtained from in vitro trypsin degradation indicated that with the increase of GA concentration and reaction time, the degradation rate decreased. From thermogravimetry and differential scanning calorimetry analysis it can be observed that the collagen in the matrices becomes more resistant to thermal degradation as a consequence of the increasing crosslink degree. Scanning electron microscopy analysis indicated that after the GA crosslinking, collagen fibers become more organized and well-defined. Therefore, the preparations of porcine skin matrices with different degradation rates, which can be used in soft tissue reconstruction, are viable.

INFERENCE FOR EIGENVALUES AND EIGENVECTORS OF GAUSSIAN SYMMETRIC MATRICES

This article presents maximum likelihood estimators (MLEs) and log-likelihood ratio (LLR) tests for the eigenvalues and eigenvectors of Gaussian random symmetric matrices of arbitrary dimension, where the observations are independent repeated samples from one or two populations. These inference problems are relevant in the analysis of diffusion tensor imaging data and polarized cosmic background radiation data, where the observations are, respectively, 3 x 3 and 2 x 2 symmetric positive definite matrices. The parameter sets involved in the inference problems for eigenvalues and eigenvectors are subsets of Euclidean space that are either affine subspaces, embedded submanifolds that are invariant under orthogonal transformations or polyhedral convex cones. We show that for a class of sets that includes the ones considered in this paper, the MLEs of the mean parameter do not depend on the covariance parameters if and only if the covariance structure is orthogonally invariant. Closed-form expressions for the MLEs and the associated LLRs are derived for this covariance structure.

Constant-random practice and the adaptive process in motor learning with varying amounts of constant practice

The adaptive process in motor learning was examined in terms of effects of varying amounts of constant practice performed before random practice. Participants pressed five response keys sequentially, the last one coincident with the lighting of a final visual stimulus provided by a complex coincident timing apparatus. Different visual stimulus speeds were used during the random practice. 33 children (M age=11.6 yr.) were randomly assigned to one of three experimental groups: constant-random, constant-random 33%, and constant-random 66%. The constant-random group practiced constantly until they reached a criterion of performance stabilization three consecutive trials within 50 msec. of error. The other two groups had additional constant practice of 33 and 66%, respectively, of the number of trials needed to achieve the stabilization criterion. All three groups performed 36 trials under random practice; in the adaptation phase, they practiced at a different visual stimulus speed adopted in the stabilization phase. Global performance measures were absolute, constant, and variable errors, and movement pattern was analyzed by relative timing and overall movement time. There was no group difference in relation to global performance measures and overall movement time. However, differences between the groups were observed on movement pattern, since constant-random 66% group changed its relative timing performance in the adaptation phase.

Influence of gelation time on the morphological and physico-chemical properties of the sol-gel entrapped lipase

Different gelation times (4, 18, 24 and 48 h) were used for the preparation of silica sol-gel supports and encapsulated Candida rugosa lipase using tetraethoxysilane (TEOS) as precursor. The hydrophobic matrices and immobilized lipases produced were characterized with regard to pore volume and size by nitrogen adsorption (BJH method), weight loss upon heating (TGA), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), chemical composition (FTIR) and percentage of hydrolysis (POH%) of olive oil. These structural parameters were found to change with the gelation time, but no direct relation was found between the percentage of oil hydrolysis (POH%) and the gelation time. The best combination of high thermal stability and high POH% (99.5%) occurred for encapsulated lipase produced with 24 h gelation time. (C) 2007 Elsevier B.V. All rights reserved.

Biohydrogen production in anaerobic fluidized bed reactors: Effect of support material and hydraulic retention time

This study evaluated two different support materials (polystyrene and expanded clay) for biohydrogen production in an anaerobic fluidized bed reactor (AFBR) treating synthetic wastewater containing glucose (4000 mg L(-1)). The AFBRs contained either polystyrene (R1) or expanded clay (R2) as support materials were inoculated with thermally pre-treated anaerobic sludge and operated at a temperature of 30 degrees C and a pH of approximately 5.5. The AFBRs were operated with a range of hydraulic retention times (HRTs) between 1 and 8 h. For R1 with an HRT of 2 h, the maximum hydrogen yield (HY) was 1.90 mol H(2) mol(-1) glucose, with 0.805 mg of biomass (as total volatile solids, or TVS) attached to each g of polystyrene. For R2 operated at an HRT of 2 h, the maximum HY was 2.59 mol H(2) moll glucose, with 1.100 mg of attached biomass (as TVS) g(-1) expanded clay. The highest hydrogen production rates (HPR) were 0.95 and 1.21 L h(-1) L(-1) for R1 and R2, respectively, using an HRT of 1 h. The H(2) content increased from 16-47% for R1 and from 22-51% for R2. No methane was detected in the biogas produced throughout the period of AFBR operation. These results show that the values of HY, HPR, H(2) content, and g of attached biomass g(-1) support material were all higher for AFBRs containing expanded clay than for reactors containing polystyrene. (C) 2010 Professor T. Nejat Veziroglu. Published by Elsevier Ltd. All rights reserved.

A Separation Principle for the Continuous-Time LQ-Problem With Markovian Jump Parameters

In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.