Generalized Coupled Algebraic Riccati Equations for Discrete-time Markov Jump with Multiplicative Noise Systems

In this paper we consider the existence of the maximal and mean square stabilizing solutions for a set of generalized coupled algebraic Riccati equations (GCARE for short) associated to the infinite-horizon stochastic optimal control problem of discrete-time Markov jump with multiplicative noise linear systems. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. We present a sufficient condition, based only on some positive semi-definite and kernel restrictions on some matrices, under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution fir the GCARE. We also present a solution for the discounted and long run average cost problems when the performance criterion is assumed be composed by a linear combination of an indefinite quadratic part and a linear part in the state and control variables. The paper is concluded with a numerical example for pension fund with regime switching.

A generalized multi-period mean-variance portfolio optimization with Markov switching parameters

In this paper, we deal with a generalized multi-period mean-variance portfolio selection problem with market parameters Subject to Markov random regime switchings. Problems of this kind have been recently considered in the literature for control over bankruptcy, for cases in which there are no jumps in market parameters (see [Zhu, S. S., Li, D., & Wang, S. Y. (2004). Risk control over bankruptcy in dynamic portfolio selection: A generalized mean variance formulation. IEEE Transactions on Automatic Control, 49, 447-457]). We present necessary and Sufficient conditions for obtaining an optimal control policy for this Markovian generalized multi-period meal-variance problem, based on a set of interconnected Riccati difference equations, and oil a set of other recursive equations. Some closed formulas are also derived for two special cases, extending some previous results in the literature. We apply the results to a numerical example with real data for Fisk control over bankruptcy Ill a dynamic portfolio selection problem with Markov jumps selection problem. (C) 2008 Elsevier Ltd. All rights reserved.

The generalized inverse Weibull distribution

The inverse Weibull distribution has the ability to model failure rates which are quite common in reliability and biological studies. A three-parameter generalized inverse Weibull distribution with decreasing and unimodal failure rate is introduced and studied. We provide a comprehensive treatment of the mathematical properties of the new distribution including expressions for the moment generating function and the rth generalized moment. The mixture model of two generalized inverse Weibull distributions is investigated. The identifiability property of the mixture model is demonstrated. For the first time, we propose a location-scale regression model based on the log-generalized inverse Weibull distribution for modeling lifetime data. In addition, we develop some diagnostic tools for sensitivity analysis. Two applications of real data are given to illustrate the potentiality of the proposed regression model.

Extensions of discrete triangular distributions and boundary bias in kernel estimation for discrete functions

Asymmetric discrete triangular distributions are introduced in order to extend the symmetric ones serving for discrete associated kernels in the nonparametric estimation for discrete functions. The extension from one to two orders around the mode provides a large family of discrete distributions having a finite support. Establishing a bridge between Dirac and discrete uniform distributions, some different shapes are also obtained and their properties are investigated. In particular, the mean and variance are pointed out. Applications to discrete kernel estimators are given with a solution to a boundary bias problem. (C) 2010 Elsevier B.V. All rights reserved.

The beta modified Weibull distribution

A five-parameter distribution so-called the beta modified Weibull distribution is defined and studied. The new distribution contains, as special submodels, several important distributions discussed in the literature, such as the generalized modified Weibull, beta Weibull, exponentiated Weibull, beta exponential, modified Weibull and Weibull distributions, among others. The new distribution can be used effectively in the analysis of survival data since it accommodates monotone, unimodal and bathtub-shaped hazard functions. We derive the moments and examine the order statistics and their moments. We propose the method of maximum likelihood for estimating the model parameters and obtain the observed information matrix. A real data set is used to illustrate the importance and flexibility of the new distribution.

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

A generalized modified Weibull distribution for lifetime modeling

A four parameter generalization of the Weibull distribution capable of modeling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone as well as non-monotone failure rates, which are quite common in lifetime problems and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh and modified Weibull distributions, among others. We derive two infinite sum representations for its moments. The density of the order statistics is obtained. The method of maximum likelihood is used for estimating the model parameters. Also, the observed information matrix is obtained. Two applications are presented to illustrate the proposed distribution. (C) 2008 Elsevier B.V. All rights reserved.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

Effects of chlorogenic acid on neutrophil locomotion functions in response to inflammatory stimulus

Aim of the study: Species of Lychnophora are used in Brazilian folk medicine as analgesic and anti-inflammatory agents. Chlorogenic acid (CGA) and their analogues are important components of polar extracts of these species, as well in several European and Asian medicinal plants. Some of these phenolic compounds display anti-inflammatory effects. In this paper we report the isolation of CGA from Lychnophora salicifolia and its effects on functions involved in neutrophils locomotion. Materials and methods: LC-MS(n) data confirmed the presence of CGA in the plant. Actions of CGA were investigated on neutrophils obtained from peritoneal cavity of Wistar rats (4h after 1% oyster glycogen solution injection; 10 ml), and incubated with vehicle or with 50, 100 or 1000 mu M CGA in presence of lipopolysaccharide from Escherichia coil (LPS, 5 mu g/ml). Nitric oxide (NO; Griess reaction); prostaglandin E(2) (PGE(2)), interleukin-1 beta (IL-1 beta) and tumor necrosis factor-alpha [TNF-alpha; enzyme-linked immunosorbent assay (EIA)]; protein (flow cytometry) and gene (RT-PCR) expression of L-selectin, beta(2)integrin and platelet-endothelial cell adhesion molecule-1 (PECAM-1) were quantified. In vitro neutrophil adhesion to primary culture of microvascular endothelial cell (PMEC) and neutrophil migration in response to formyl-methionil-leucil-phenilalanine (fMLP, 10(-8)M, Boyden chamber) was determined. Results: CGA treatment did not modify the secretion of inflammatory mediators, but inhibited L-selectin cleavage and reduced beta(2) integrin, independently from its mRNA synthesis, and reduced membrane PECAM-1 expression: inhibited neutrophil adhesion and neutrophil migration induced by fMLP. Conclusions: Based on these findings, we highlight the direct inhibitory actions of CGA on adhesive and locomotion properties of neutrophils, which may contribute to its anti-inflammatory effects and help to explain the use of Lychnophora salicifolia as an anti-inflammatory agent. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Effects of methylmercury on male reproductive functions in Wistar rats

In this study we investigated the effects of subacute exposure to methylmercury (MeHg) on male reproductive functions in rats by means of determination of alterations in structural and functional parameters. Adult male Wistar rats received 0, 0.5, 1.0 or 3.0 mg/kg/body weight/day orally, daily MeHg for 14 days. Sperm motility, the relative sperm count and transit time in the caput/corpus epididymis, were all reduced at all doses. The lowest dose increased the number of sperm head abnormalities; daily sperm production was elevated at the intermediate dose; while at the highest dose there was a decrease in serum testosterone levels and a rise in mercury (Hg) content in reproductive organs, liver and kidneys. In conclusion, MeHg exposure produced damages on male reproductive functions which may be attributed, at least in part, to the reduction in serum testosterone levels. These consequences could potentially result in infertility in rats. (C) 2011 Elsevier Inc. All rights reserved.

Modal functions of future tenses in French

The paper disputes two influential claims in the Romance Linguistics literature. The first is that the synthetic future tenses in spoken Western Romance are now rivalled, if not supplanted, as temporal functors by the more recently developed GO futures. The second is that these synthetic futures now have modal rather than temporal meanings in spoken Romance. These claims are seen as reflecting a universal cycle of diachronic change, in which verb forms originally expressing modal (or aspectual) values take on future temporal reference, becoming tenses. The new modal meanings supplant the temporal, which are then taken up by new forms. Challenges to this theory for French are raised on the basis of empirical evidence of two sorts. Positively, future tenses in spoken Romance continue to be used with temporal meaning. Negatively, evidence of modal meaning for these forms is lacking. The evidence comes froma corpora of spoken French, native speaker judgements and verb data from a daily broadsheet. Cumulatively, it points to the reverse of the claims noted above: the synthetic future in spoken French has temporal but little modal meaning.

Sampling phylogenetic tree space with the generalized Gibbs sampler

The generalized Gibbs sampler (GGS) is a recently developed Markov chain Monte Carlo (MCMC) technique that enables Gibbs-like sampling of state spaces that lack a convenient representation in terms of a fixed coordinate system. This paper describes a new sampler, called the tree sampler, which uses the GGS to sample from a state space consisting of phylogenetic trees. The tree sampler is useful for a wide range of phylogenetic applications, including Bayesian, maximum likelihood, and maximum parsimony methods. A fast new algorithm to search for a maximum parsimony phylogeny is presented, using the tree sampler in the context of simulated annealing. The mathematics underlying the algorithm is explained and its time complexity is analyzed. The method is tested on two large data sets consisting of 123 sequences and 500 sequences, respectively. The new algorithm is shown to compare very favorably in terms of speed and accuracy to the program DNAPARS from the PHYLIP package.

Polytomous item response theory models

Polytomous Item Response Theory Models provides a unified, comprehensive introduction to the range of polytomous models available within item response theory (IRT). It begins by outlining the primary structural distinction between the two major types of polytomous IRT models. This focuses on the two types of response probability that are unique to polytomous models and their associated response functions, which are modeled differently by the different types of IRT model. It describes, both conceptually and mathematically, the major specific polytomous models, including the Nominal Response Model, the Partial Credit Model, the Rating Scale model, and the Graded Response Model. Important variations, such as the Generalized Partial Credit Model are also described as are less common variations, such as the Rating Scale version of the Graded Response Model. Relationships among the models are also investigated and the operation of measurement information is described for each major model. Practical examples of major models using real data are provided, as is a chapter on choosing an appropriate model. Figures are used throughout to illustrate important elements as they are described.