Forecasting with Vector Nonlinear Time Series Models

This work concerns forecasting with vector nonlinear time series models when errorsare correlated. Point forecasts are numerically obtained using bootstrap methods andillustrated by two examples. Evaluation concentrates on studying forecast equality andencompassing. Nonlinear impulse responses are further considered and graphically sum-marized by highest density region. Finally, two macroeconomic data sets are used toillustrate our work. The forecasts from linear or nonlinear model could contribute usefulinformation absent in the forecasts form the other model.

Residual-based Inference for Common Nonlinear Features

This paper investigates common nonlinear features in multivariate nonlinear autore-gressive models via testing the estimated residuals. A Wald-type test is proposed and itis asymptotically Chi-squared distributed. Simulation studies are given to examine thefinite-sample properties of the proposed test.

Exploratory semiparametric analysis of two-dimensional diffusions in finance

We examine bivariate extensions of Aït-Sahalia’s approach to the estimation of univariate diffusions. Our message is that extending his idea to a bivariate setting is not straightforward. In higher dimensions, as opposed to the univariate case, the elements of the Itô and Fokker-Planck representations do not coincide; and, even imposing sensible assumptions on the marginal drifts and volatilities is not sufficient to obtain direct generalisations. We develop exploratory estimation and testing procedures, by parametrizing the drifts of both component processes and setting restrictions on the terms of either the Itô or the Fokker-Planck covariance matrices. This may lead to highly nonlinear ordinary differential equations, where the definition of boundary conditions is crucial. For the methods developed, the Fokker-Planck representation seems more tractable than the Itô’s. Questions for further research include the design of regularity conditions on the time series dependence in the data, the kernels actually used and the bandwidths, to obtain asymptotic properties for the estimators proposed. A particular case seems promising: “causal bivariate models” in which only one of the diffusions contributes to the volatility of the other. Hedging strategies which estimate separately the univariate diffusions at stake may thus be improved.

Convergence analysis of sampling-based decomposition methods for risk-averse multistage stochastic convex programs

We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.

A narratological analysis of D. M. Thoma`s: the white hotel (1981)

“A Narratological Analysis of D. M. Thomas’s The White Hotel (1981)” originated within a seminar on British Postmodernist Literature during the first Master’s Degree in “British and North-American Culture and Literature” (2001-04) at the Universidade da Madeira set up by the Department of English and German Studies. This dissertation seeks to present a narratological analysis of Thomas’s novel. The White Hotel stands as a paradigmatic example of the kind of literature that has dominated the British literary scene in the past three decades, commonly referred to as postmodernist fiction, owing to its formal craftsmanship (multiplicity of narrative voices and perspectives, mixing of differing genres and text types, inclusion of embedded narratives) alongside the handling of what are deemed as postmodernist topoi (the distinction between truth and lies, history and fantasy, fact and fiction, the questioning of the nature of aesthetic representation, the role the author and the reader hold in the narrative process, the instability of the linguistic sign, the notion of originality and the moral responsibility the author has towards his/her work), The narratological approach carried out in this research reveals that Thomas’s text constitutes an aesthetic endeavour to challenge the teleological drive that is inherent in any narrative, i. e., the inevitable progression towards a reassuring end. Hence, the subversion of narrative telling, which is a recurrent feature in Thomas’s remaining literary output, mirrors the contemporary distrust in totalising, hierarchised and allencompassing narratives. In its handling of historical events, namely of the Holocaust, The White Hotel invites us to reassess the most profound beliefs we were taught to take for granted: progress, reality and truth. In their place the novel proposes a more flexible conception of both the world and art, especially of literary fiction. In other terms, the world appears as a brutal chaotic place the subject is forced to adjust to. Accordingly, the literary work is deemed hybrid, fragmented and open. So as to put forth the above-mentioned issues, this research work is structured in three main chapters. The initial chapter – “What is Postmodernism?” – advances a scrutiny not only of the seminal but also of more recent studies on postmodernist literary criticism. Following this, in Chapter II – “Postmodernist British Fiction” – a brief overview of postmodernist British fiction is carried out, focusing on the fictional works that, in my opinion, are fundamental for the periodising of British postmodernism. In addition, I felt the need to include a section – “D. M. Thomas as a Postmodernist Novelist” – in which the author’s remaining literary output is briefly examined. Finally, Chapter III – “A Narratological Analysis of The White Hotel” – proposes a narratological analysis of the novel according to the particular Genettian analytical model. To conclude, my dissertation constitutes an approach to D. M. Thomas’s The White Hotel as a text whose very existence is substantiated in the foregrounding of the contingency of all discourses, meeting the postmodernist precepts of openness and subversion of any narrative that claims to be true, globalising and all-inclusive.

Egg production curve fitting using nonlinear models for selected and nonselected lines of White Leghorn hens

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Models for the analysis of growth curves for rearing tinamous (Rhynchotus rufescens) in captivity

Growth curves models provide a visual assessment of growth as a function of time, and prediction body weight at a specific age. This study aimed at estimating tinamous growth curve using different models, and at verifying their goodness of fit. A total number 11,639 weight records from 411 birds, being 6,671 from females and 3,095 from males, was analyzed. The highest estimates of a parameter were obtained using Brody (BD), von Bertalanffy (VB), Gompertz (GP,) and Logistic function (LG). Adult females were 5.7% heavier than males. The highest estimates of b parameter were obtained in the LG, GP, BID, and VB models. The estimated k parameter values in decreasing order were obtained in LG, GP, VB, and BID models. The correlation between the parameters a and k showed heavier birds are less precocious than the lighter. The estimates of intercept, linear regression coefficient, quadratic regression coefficient, and differences between quadratic coefficient of functions and estimated ties of quadratic-quadratic-quadratic segmented polynomials (QQQSP) were: 31.1732 +/- 2.41339; 3.07898 +/- 0.13287; 0.02689 +/- 0.00152; -0.05566 +/- 0.00193; 0.02349 +/- 0.00107, and 57 and 145 days, respectively. The estimated predicted mean error values (PME) of VB, GP, BID, LG, and QQQSP models were, respectively, 0.8353; 0.01715; -0.6939; -2.2453; and -0.7544%. The coefficient of determination (RI) and least square error values (MS) showed similar results. In conclusion, the VB and the QQQSP models adequately described tinamous growth. The best model to describe tinamous growth was the Gompertz model, because it presented the highest R-2 values, easiness of convergence, lower PME, and the easiness of parameter biological interpretation.

Comparison of different nonlinear functions to describe Nelore cattle growth

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Time-periodic perturbation of a Lienard equation with an unbounded homoclinic loop

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Global dynamics of the Rikitake system

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Bifurcation Analysis of a Van der Pol-Duffing Circuit with Parallel Resistor

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Determination of the numerical parameters of a continuous damage model for the structural analysis of clay brick masonry

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

About the Use of the HdHr Algorithm Group in Integrating the Movement Equation with Nonlinear Terms

This work summarizes the HdHr group of Hermitian integration algorithms for dynamic structural analysis applications. It proposes a procedure for their use when nonlinear terms are present in the equilibrium equation. The simple pendulum problem is solved as a first example and the numerical results are discussed. Directions to be pursued in future research are also mentioned. Copyright (C) 2009 H.M. Bottura and A. C. Rigitano.

Modeling and analysis of artificial neural networks applied in operations research

Artificial neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements. Systems based on artificial neural networks have high computational rates due to the use of a massive number of these computational elements. Neural networks with feedback connections provide a computing model capable of solving a rich class of optimization problems. In this paper, a modified Hopfield network is developed for solving problems related to operations research. The internal parameters of the network are obtained using the valid-subspace technique. Simulated examples are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

An analysis of the region of the Phocaea dynamical family

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)