Algebraic derivative estimation applied to nonlinear control of magnetic levitation.

The subject of this thesis is the real-time implementation of algebraic derivative estimators as observers in nonlinear control of magnetic levitation systems. These estimators are based on operational calculus and implemented as FIR filters, resulting on a feasible real-time implementation. The algebraic method provide a fast, non-asymptotic state estimation. For the magnetic levitation systems, the algebraic estimators may replace the standard asymptotic observers assuring very good performance and robustness. To validate the estimators as observers in closed-loop control, several nonlinear controllers are proposed and implemented in a experimental magnetic levitation prototype. The results show an excellent performance of the proposed control laws together with the algebraic estimators.

Estimação do índice de memória em processos estocásticos com memória longa: uma abordagem via ABC

Neste trabalho propomos o uso de um método Bayesiano para estimar o parâmetro de memória de um processo estocástico com memória longa quando sua função de verossimilhança é intratável ou não está disponível. Esta abordagem fornece uma aproximação para a distribuição a posteriori sobre a memória e outros parâmetros e é baseada numa aplicação simples do método conhecido como computação Bayesiana aproximada (ABC). Alguns estimadores populares para o parâmetro de memória serão revisados e comparados com esta abordagem. O emprego de nossa proposta viabiliza a solução de problemas complexos sob o ponto de vista Bayesiano e, embora aproximativa, possui um desempenho muito satisfatório quando comparada com métodos clássicos.

Portfolio efficiency tests with conditioning information using empirical likelihood estimation

We evaluate the use of Generalized Empirical Likelihood (GEL) estimators in portfolios efficiency tests for asset pricing models in the presence of conditional information. Estimators from GEL family presents some optimal statistical properties, such as robustness to misspecification and better properties in finite samples. Unlike GMM, the bias for GEL estimators do not increase as more moment conditions are included, which is expected in conditional efficiency analysis. We found some evidences that estimators from GEL class really performs differently in small samples, where efficiency tests using GEL generate lower estimates compared to tests using the standard approach with GMM. With Monte Carlo experiments we see that GEL has better performance when distortions are present in data, especially under heavy tails and Gaussian shocks.

Estimação e previsão no processo INARCH(2)

In the last decades the study of integer-valued time series has gained notoriety due to its broad applicability (modeling the number of car accidents in a given highway, or the number of people infected by a virus are two examples). One of the main interests of this area of study is to make forecasts, and for this reason it is very important to propose methods to make such forecasts, which consist of nonnegative integer values, due to the discrete nature of the data. In this work, we focus on the study and proposal of forecasts one, two and h steps ahead for integer-valued second-order autoregressive conditional heteroskedasticity processes [INARCH (2)], and in determining some theoretical properties of this model, such as the ordinary moments of its marginal distribution and the asymptotic distribution of its conditional least squares estimators. In addition, we study, via Monte Carlo simulation, the behavior of the estimators for the parameters of INARCH(2) processes obtained using three di erent methods (Yule- Walker, conditional least squares, and conditional maximum likelihood), in terms of mean squared error, mean absolute error and bias. We present some forecast proposals for INARCH(2) processes, which are compared again via Monte Carlo simulation. As an application of this proposed theory, we model a dataset related to the number of live male births of mothers living at Riachuelo city, in the state of Rio Grande do Norte, Brazil.

Estimação e previsão no processo INARCH(2)

In the last decades the study of integer-valued time series has gained notoriety due to its broad applicability (modeling the number of car accidents in a given highway, or the number of people infected by a virus are two examples). One of the main interests of this area of study is to make forecasts, and for this reason it is very important to propose methods to make such forecasts, which consist of nonnegative integer values, due to the discrete nature of the data. In this work, we focus on the study and proposal of forecasts one, two and h steps ahead for integer-valued second-order autoregressive conditional heteroskedasticity processes [INARCH (2)], and in determining some theoretical properties of this model, such as the ordinary moments of its marginal distribution and the asymptotic distribution of its conditional least squares estimators. In addition, we study, via Monte Carlo simulation, the behavior of the estimators for the parameters of INARCH(2) processes obtained using three di erent methods (Yule- Walker, conditional least squares, and conditional maximum likelihood), in terms of mean squared error, mean absolute error and bias. We present some forecast proposals for INARCH(2) processes, which are compared again via Monte Carlo simulation. As an application of this proposed theory, we model a dataset related to the number of live male births of mothers living at Riachuelo city, in the state of Rio Grande do Norte, Brazil.

Efeitos da internacionalização no desvio da estrutura de capital alvo e na velocidade de ajuste

This dissertation investigates the effects of internationalization in two gaps related to the capital structure that have not been discussed by the Brazilian literature yet. To this, were developed two independent sections. The first examined what the effects of internationalization on the deviation from the target capital structure. The second examined what the effects of internationalization on speed of adjustment (SOA) of the capital structure. It used data from Brazil, multinational and domestic companies, from 2006 to 2014. The results of the first analysis indicate that internationalization helps reduce the difference between the target and the current debt. That is, to the extent that the level of internationalization increases; whether only export or a combination of export, assets and employees abroad, the gap between the current structure and the target structure decreases. This reduction is given as a function of internationalization as a consequence of the upstream effect of the upstream-downstream hypothesis. Thus, as the Market Timing theory, it can be seen as an opportunity for adjustment of the capital structure, and with the reduction of deviation, there is also a reduction in the cost of capital of the firm. The result of the second analysis indicates that internationalization is able to significantly increase the speed adjustment, ensuring for the multinational a faster adjustment of its capital structure. Exports increase the SOA in 9 to 23%. And when also kept active assets and employees abroad the increase is 8 to 20%. In terms of time, while domestic company takes more than three years to reduce half of the deviation that has, while multinacional companies take on average one and a half year to reduce the same proportion of the deviation. The validity of the upstream-downstream hypothesis for the effect of internationalization in SOA was confirmed by comparing the results for US companies. Thus, the phenomenon of internationalization increases SOA when companies are from less stable markets, such as Brazil; and it has a less significcative effect when companies are derived from more stable markets, because they already have a high speed of adjustmennt. In addition, the adequacy analysis of the estimators also showed the model pooled OLS (Ordinary Least Squares) presents the highest quality in predicting the SOA than the system GMM (Generalized Method of Moments). For future studies it is suggested to analyze the effect of international event, by itself, and to validate the hypothesis using samples of different markets and the use of other estimators.

Bayesian estimation in generalized autoregressive conditional heteroskedasticity models

Esta tesis doctoral nace con el propósito de entender, analizar y sobre todo modelizar el comportamiento estadístico de las series financieras. En este sentido, se puede afirmar que los modelos que mejor recogen las especiales características de estas series son los modelos de heterocedasticidad condicionada en tiempo discreto,si los intervalos de tiempo en los que se recogen los datos lo permiten, y en tiempo continuo si tenemos datos diarios o datos intradía. Con esta finalidad, en esta tesis se proponen distintos estimadores bayesianos para la estimación de los parámetros de los modelos GARCH en tiempo discreto (Bollerslev (1986)) y COGARCH en tiempo continuo (Kluppelberg et al. (2004)). En el capítulo 1 se introducen las características de las series financieras y se presentan los modelos ARCH, GARCH y COGARCH, así como sus principales propiedades. Mandelbrot (1963) destacó que las series financieras no presentan estacionariedad y que sus incrementos no presentan autocorrelación, aunque sus cuadrados sí están correlacionados. Señaló también que la volatilidad que presentan no es constante y que aparecen clusters de volatilidad. Observó la falta de normalidad de las series financieras, debida principalmente a su comportamiento leptocúrtico, y también destacó los efectos estacionales que presentan las series, analizando como se ven afectadas por la época del año o el día de la semana. Posteriormente Black (1976) completó la lista de características especiales incluyendo los denominados leverage effects relacionados con como las fluctuaciones positivas y negativas de los precios de los activos afectan a la volatilidad de las series de forma distinta.

Sincronização em OFDM

Esta dissertação apresenta o trabalho sobre sincronização de receção para sistemas OFDM. Tendo como objetivo a integração da arquitetura desenvolvida no projeto de investigação \CROWN - Co-operative Radio over Fibre for Wireless Networks" atualmente em curso no Instituto de Telecomunicações. Esta arquitetura de receção foi implementada numa plataforma de desenvolvimento baseada em dispositivos programáveis FPGA, recorrendo as ferramentas de desenvolvimento MatLab, System Generator e ISE. O sistema implementado tem a particularidade de ter um princípio de funcionamento assíncrono e recorre aos algoritmos de Van de Beek [1] e Carlos Ribeiro [2] para proceder a estimação e consequente sincronização. Ambos os algoritmos foram utilizados para estimação do CFO, tendo o algoritmo de Van de Beek sido também utilizado para estimação do início de trama. Foram realizadas análises do desempenho do sistema para diferentes condições, sendo o objectivo de analisar o desempenho dos estimadores implementados. A performance foi então analisada de acordo com BER resultante e do erro de estimação do início de trama e do valor do CFO. Para além da análise individual dos resultados, e também feita uma comparação da precisão de ambos os estimadores.

Estimate of the (R)USLE rainfall erosivity factor from monthly precipitation data in mainland Spain

The need for continuous recording rain gauges makes it difficult to determine the rainfall erosivity factor (R-factor) of the (R)USLE model in areas without good temporal data coverage. In mainland Spain, the Nature Conservation Institute (ICONA) determined the R-factor at few selected pluviographs, so simple estimates of the R-factor are definitely of great interest. The objectives of this study were: (1) to identify a readily available estimate of the R-factor for mainland Spain; (2) to discuss the applicability of a single (global) estimate based on analysis of regional results; (3) to evaluate the effect of record length on estimate precision and accuracy; and (4) to validate an available regression model developed by ICONA. Four estimators based on monthly precipitation were computed at 74 rainfall stations throughout mainland Spain. The regression analysis conducted at a global level clearly showed that modified Fournier index (MFI) ranked first among all assessed indexes. Applicability of this preliminary global model across mainland Spain was evaluated by analyzing regression results obtained at a regional level. It was found that three contiguous regions of eastern Spain (Catalonia, Valencian Community and Murcia) could have a different rainfall erosivity pattern, so a new regression analysis was conducted by dividing mainland Spain into two areas: Eastern Spain and plateau-lowland area. A comparative analysis concluded that the bi-areal regression model based on MFI for a 10-year record length provided a simple, precise and accurate estimate of the R-factor in mainland Spain. Finally, validation of the regression model proposed by ICONA showed that R-ICONA index overpredicted the R-factor by approximately 19%.

FLORÍSTICA E ESTRUTURA DO COMPONENTE ARBÓREO E RELAÇÃO COM VARIÁVEIS AMBIENTAIS EM UM REMANESCENTE FLORESTAL EM CAMPOS NOVOS - SC

O presente estudo objetivou conhecer os padrões da composição florística e estrutural do componente arbóreo de um trecho de remanescente de Floresta Ombrófila Mista Montana em Campos Novos - SC e determinar as variáveis ambientais que influenciam estes padrões. Para isso, foi amostrado 1 ha de floresta por meio de 50 parcelas de 10 × 20 m dispostas de forma sistemática, distanciada 30 m entre si, no remanescente florestal. Dentro das parcelas foram identificados e mensurados (circunferência medida a altura do peito, CAP, e altura total) CAP, e altura total) todos os indivíduos arbóreos vivos com CAP ≥ 15,7 cm. Os dados ambientais relacionados às propriedades químicas e físicas dos solos e à topografia também foram coletados em cada parcela. Foram calculados o índice de Shannon-Wiener (H’), a equabilidade de Pielou (J’) e os estimadores fitossociológicos. A organização florístico-estrutural do fragmento foi analisada por meio de uma NMDS (Nonmetric multidimensional scalling). As variáveis ambientais foram ajustadas a posteriori à ordenaçã o produzida, sendo aquelas significativas (p < 0,05) plotadas na forma de vetores. Foram amostrados 1.027 indivíduos, que totalizaram uma área basal de 43,57 m2, distribuídos em 88 espécies e 41 famílias botânicas. A diversidade do remanescente estudado foi relativamente alta (H’=3,59) e a dominância baixa (J’=0,80). A espécie de maior VI foi Araucaria angustifolia (Bertol.) Kuntze (14,44%). A análise multivariada NMDS indicou um gradiente florístico-estrutural relacionado à cota média (altitude), saturação de bases, pH e teores de P nos solos.

Modeling height-diameter relationship in pinus pinaster ait. in the forest intervention zone of Lomba, NE-Portugal

In this work, the relationship between diameter at breast height (d) and total height (h) of individual-tree was modeled with the aim to establish provisory height-diameter (h-d) equations for maritime pine (Pinus pinaster Ait.) stands in the Lomba ZIF, Northeast Portugal. Using data collected locally, several local and generalized h-d equations from the literature were tested and adaptations were also considered. Model fitting was conducted by using usual nonlinear least squares (nls) methods. The best local and generalized models selected, were also tested as mixed models applying a first-order conditional expectation (FOCE) approximation procedure and maximum likelihood methods to estimate fixed and random effects. For the calibration of the mixed models and in order to be consistent with the fitting procedure, the FOCE method was also used to test different sampling designs. The results showed that the local h-d equations with two parameters performed better than the analogous models with three parameters. However a unique set of parameter values for the local model can not be used to all maritime pine stands in Lomba ZIF and thus, a generalized model including covariates from the stand, in addition to d, was necessary to obtain an adequate predictive performance. No evident superiority of the generalized mixed model in comparison to the generalized model with nonlinear least squares parameters estimates was observed. On the other hand, in the case of the local model, the predictive performance greatly improved when random effects were included. The results showed that the mixed model based in the local h-d equation selected is a viable alternative for estimating h if variables from the stand are not available. Moreover, it was observed that it is possible to obtain an adequate calibrated response using only 2 to 5 additional h-d measurements in quantile (or random) trees from the distribution of d in the plot (stand). Balancing sampling effort, accuracy and straightforwardness in practical applications, the generalized model from nls fit is recommended. Examples of applications of the selected generalized equation to the forest management are presented, namely how to use it to complete missing information from forest inventory and also showing how such an equation can be incorporated in a stand-level decision support system that aims to optimize the forest management for the maximization of wood volume production in Lomba ZIF maritime pine stands.

Intervalo de confiança para o parâmetro estimado pelo estimador de Horvitz-Thompson

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Estatística, 2016.

Curvas de crescimiento de una alga bioindicadora expuesta a diferentes tratamientos: uso de modelos lineales y no lineales.

Los modelos no lineales son ampliamente utilizados para describir curvas de crescimiento. En un modelo no lineal, Y=f(t,0)+E donde Y es el vector de observaciones, t el vector correspondiente a las condiciones de evaluacion (instantes de tiempo conocidos), 0 el vector de parametros desconocidos, f(.) una funcion no lineal en 0 y E el vector de errores, comunmente se asume que E ~ N(O,sigma ao quadrado I). Cuando no se cumplen algunos aspectos de esa suposicion (normalidad, independencia y homogeneidad de variancias), la normalidad asintotica de los estimadores de interes puede ser afectada dificultando la comparacion de curvas obtenidas en los diferentes tratamentos. En organismos unicelulares, tales como las algas, el crecimiento es comumente medido a travez de la observacion del numero de celulas N1, N2,...,Nk en los instantes t1, t2,...,tk., respectivamente. Variables de esa naturaleza, geralmente modeladas por la distribuicion de Poisson, tienen variancias iguales a las respectivas esperanzas (crescientes con el tiempo), no verificando-se la de suposicion de homocedasticidad, lo que inviabiliza la utilizacion del modelo anteriormente descrito. El objetivo de este trabajo es discutir aspectos relacionados al uso adecuado de los modelos lineales y no lineales en el ajuste de curvas de crecimiento donde la variable respuesta tiene distribucion de Poisson. Como ejemplo, son utilizados datos de crecimiento de la microalga bioindicadora Selenastrumcapricornutum, la cual fue expuesta a diferentes tratamientos (con y sin un biopesticidas) en condiciones de laboratorio. En tales casos, donde la transformacion logaritmica de la respuesta linealiza la relacion numero de celulas versus tiempo, ademas de homogeneizar las variancias, el uso de un modelo lineal es adecuado.

Determinación del comportamiento del riesgo cardiovascular en paciente postrasplante hepatico en Fundacion Cardioinfantil

El trasplante hepático es una opción terapéutica para enfermedad hepática avanzada cada vez más frecuente en Colombia. La sobrevida del 80% a 5 años conlleva a un aumento del riesgo cardiovascular y de eventos cardiovasculares, por esta razón esta investigación determina el comportamiento del riesgo cardiovascular en los pacientes con trasplante hepático de la Fundación Cardioinfantil, realizado en 3 años de seguimiento . Lo encontrado en esta investigación es que existe un aumento del riesgo cardiovascular a tres años en pacientes post trasplante hepático, estadísticamente significativo, principalmente secundario a hipertensión, diabetes e hipertrigliceridemia. El aumento es mayor a lo descrito en la población general, y similar a otros pacientes trasplantados, en un periodo de 5 años

Avaliação de métodos de estimação da variância em amostras complexas

A necessidade de conhecer uma população impulsiona um processo de recolha e análise de informação. Usualmente é muito difícil ou impossível estudar a totalidade da população, daí a importância do estudo com recurso a amostras. Conceber um estudo por amostragem é um processo complexo, desde antes da recolha dos dados até a fase de análise dos mesmos. Na maior parte dos estudos utilizam-se combinações de vários métodos probabilísticos de amostragem para seleção de uma amostra, que se pretende representativa da população, denominado delineamento de amostragem complexo. O conhecimento dos erros de amostragem é necessário à correta interpretação dos resultados de inquéritos e à avaliação dos seus planos de amostragem. Em amostras complexas, têm sido usadas aproximações ajustadas à natureza complexa do plano da amostra para a estimação da variância, sendo as mais utilizadas: o método de linearização Taylor e as técnicas de reamostragem e replicação. O principal objetivo deste trabalho é avaliar o desempenho dos estimadores usuais da variância em amostras complexas. Inspirado num conjunto de dados reais foram geradas três populações com características distintas, das quais foram sorteadas amostras com diferentes delineamentos de amostragem, na expectativa de obter alguma indicação sobre em que situações se deve optar por cada um dos estimadores da variância. Com base nos resultados obtidos, podemos concluir que o desempenho dos estimadores da variância da média amostral de Taylor, Jacknife e Bootstrap varia com o tipo de delineamento e população. De um modo geral, o estimador de Bootstrap é o menos preciso e em delineamentos estratificados os estimadores de Taylor e Jackknife fornecem os mesmos resultados; Evaluation of variance estimation methods in complex samples ABSTRACT: The need to know a population drives a process of collecting and analyzing information. Usually is to hard or even impossible to study the whole population, hence the importance of sampling. Framing a study by sampling is a complex process, from before the data collection until the data analysis. Many studies have used combinations of various probabilistic sampling methods for selecting a representative sample of the population, calling it complex sampling design. Knowledge of sampling errors is essential for correct interpretation of the survey results and evaluation of the sampling plans. In complex samples to estimate the variance has been approaches adjusted to the complex nature of the sample plane. The most common are: the linearization method of Taylor and techniques of resampling and replication. The main objective of this study is to evaluate the performance of usual estimators of the variance in complex samples. Inspired on real data we will generate three populations with distinct characteristics. From this populations will be drawn samples using different sampling designs. In the end we intend to get some lights about in which situations we should opt for each one of the variance estimators. Our results show that the performance of the variance estimators of sample mean Taylor, Jacknife and Bootstrap varies with the design and population. In general, the Bootstrap estimator is less precise and in stratified design Taylor and Jackknife estimators provide the same results.