Cost-effectiveness analysis is widely conducted in the economic evaluation of new treatment options. In many clinical and observational studies of costs, data are often censored. Censoring brings challenges to both medical cost estimation and cost-effectiveness analysis. Although methods have been proposed for estimating the mean costs with censored data, they are often derived from theory and it is not always easy to understand how these methods work. We provide an alternative method for estimating the mean cost more efficiently based on a replace-from-the-right algorithm, and show that this estimator is equivalent to an existing estimator based on the inverse probability weighting principle and semiparametric efficiency theory. Therefore, we provide an intuitive explanation to a theoretically derived mean cost estimator. In many applications, it is also important to estimate the survival function of costs. We propose a generalized redistribute-to-the right algorithm for estimating the survival function of costs with censored data, and show that it is equivalent to a simple weighted survival estimator of costs based on inverse probability weighting techniques. Motivated by this redistribute-to-the-right principle, we also develop a more efficient survival estimator for costs, which has the desirable property of being monotone, and more efficient, although not always consistent. We conduct simulation to compare our method with some existing survival estimators for costs, and find the bias seems quite small. Thus, it may be considered as a candidate for survival estimator for costs in a real setting when the censoring is heavy and cost history information is available. Finally, we consider one special situation in conducting cost-effectiveness analysis, when the terminating events for survival time and costs are different. Traditional methods for statistical inference cannot deal with such data. We propose a new method for deriving the confidence interval for the incremental cost-effectiveness ratio under this situation, based on counting process and the general theory for missing data process. The simulation studies show that our method performs very well for some practical settings. Our proposed method has a great potential of being applied to a real setting when different terminating events exist for survival time and costs.

In the last one hundred years, the mankind has invented a lot of convenient tools for pursuing beautiful and comfortable living environment. Computer is one of the most important inventions, and its operation ability is incomparable with the mankind. Because computer can deal with a large amount of data fast and accurately, people use this advantage to imitate human thinking. Artificial intelligence is developed extensively. Methods, such as all kinds of neural networks, data mining, fuzzy logic, etc., apply to each side fields (ex: fingerprint distinguishing, image compressing, antennal designing, etc.). We will probe into to prediction technology according to the decision tree and fuzzy clustering. The fuzzy decision tree proposed the classification method by using fuzzy clustering method, and then construct out the decision tree to predict for data. However, in the distance function, the impact of the target space was proportional inversely. This situation could make problems in some dataset. Besides, the output model of each leaf node represented by a constant restricts the representation capability about the data distribution in the node. We propose a more reasonable definition of the distance function by considering both input and target differences with weighting factor. We also extend the output model of each leaf node to a local linear model and estimate the model parameters with a recursive SVD-based least squares estimator. Experimental results have shown that our improved version produces higher recognition rates and smaller mean square errors for classification and regression problems, respectively.

In this article, we make inferences for the Weibull parameters and propose two test statistics for the comparison of two Weibull distributions based on interval-censored data. However, the distributions of the two statistics are unknown and not easy to obtain, therefore a simulation study is necessary. An urn model in the simulation of interval-censored data was proposed by Lee (1999) to select random intervals. Then we propose a simulation procedure with urn model to obtain approximately the quantiles of the two statistics. We demonstrate an example in AIDS study to illustrate how the tests can be applied to the infection time distributions of AIDS.

There are two main parts in this thesis. The first one concerns valvometry, which is here the study of the distance between both parts of the shell of an oyster, over time. The health status of oysters can be characterized using valvometry in order to obtain insights about the quality of their environment. We consider that a renewal process with four states underlies the behaviour of the studied oysters. Such a hidden process can be retrieved from a valvometric signal by assuming that some probability density function linked with this signal, is bimodal. We then compare several estimators which take this assumption into account, including kernel density estimators.In another chapter, we compare several regression approaches, aiming at analysing transcriptomic data. To understand which explanatory variables have an effect on gene expressions, we apply a multiple testing procedure on these data, through the linear model FAMT. The SIR method may find nonlinear relations in such a context. It is however more commonly used when the response variable is univariate. A multivariate version of SIR was then developed. Procedures to measure gene expressions can be expensive. The sample size n of the corresponding datasets is then often small. That is why we also studied SIR when n is less than the number of explanatory variables p.

Die letzten zwanzig Jahre haben gezeigt, dass die Integration luftgestützter Lasertechnologien (Light Detection and Ranging; LiDAR) in die Erfassung von Waldressourcen dazu beitragen kann, die Genauigkeit von Schätzungen zu erhöhen. Um diese zu ermöglichen, müssen Feldaten mit LiDAR-Daten kombiniert werden. Diverse Techniken der Modellierung bieten die Möglichkeit, diese Verbindung statistisch zu beschreiben. Während die Wahl der Methode in der Regel nur geringen Einfluss auf Punktschätzer hat, liefert sie unterschiedliche Schätzungen der Genauigkeit. In der vorliegenden Studie wurde der Einfluss verschiedener Modellierungstechniken und Variablenauswahl auf die Genauigkeit von Schätzungen untersucht. Der Schwerpunkt der Arbeit liegt hierbei auf LiDAR Anwendungen im Rahmen von Waldinventuren. Die Methoden der Variablenauswahl, welche in dieser Studie berücksichtigt wurden, waren das Akaike Informationskriterium (AIC), das korrigierte Akaike Informationskriterium (AICc), und das bayesianische (oder Schwarz) Informationskriterium. Zudem wurden Variablen anhand der Konditionsnummer und des Varianzinflationsfaktors ausgewählt. Weitere Methoden, die in dieser Studie Berücksichtigung fanden, umfassen Ridge Regression, der least absolute shrinkage and selection operator (Lasso), und der Random Forest Algorithmus. Die Methoden der schrittweisen Variablenauswahl wurden sowohl im Rahmen der Modell-assistierten als auch der Modell-basierten Inferenz untersucht. Die übrigen Methoden wurden nur im Rahmen der Modell-assistierten Inferenz untersucht. In einer umfangreichen Simulationsstudie wurden die Einflüsse der Art der Modellierungsmethode und Art der Variablenauswahl auf die Genauigkeit der Schätzung von Populationsparametern (oberirdische Biomasse in Megagramm pro Hektar) ermittelt. Hierzu wurden fünf unterschiedliche Populationen genutzt. Drei künstliche Populationen wurden simuliert, zwei weitere basierten auf in Kanada und Norwegen erhobenen Waldinveturdaten. Canonical vine copulas wurden genutzt um synthetische Populationen aus diesen Waldinventurdaten zu generieren. Aus den Populationen wurden wiederholt einfache Zufallsstichproben gezogen und für jede Stichprobe wurden der Mittelwert und die Genauigkeit der Mittelwertschätzung geschäzt. Während für das Modell-basierte Verfahren nur ein Varianzschätzer untersucht wurde, wurden für den Modell-assistierten Ansatz drei unterschiedliche Schätzer untersucht. Die Ergebnisse der Simulationsstudie zeigten, dass das einfache Anwenden von schrittweisen Methoden zur Variablenauswahl generell zur Überschätzung der Genauigkeiten in LiDAR unterstützten Waldinventuren führt. Die verzerrte Schätzung der Genauigkeiten war vor allem für kleine Stichproben (n = 40 und n = 50) von Bedeutung. Für Stichproben von größerem Umfang (n = 400), war die Überschätzung der Genauigkeit vernachlässigbar. Gute Ergebnisse, im Hinblick auf Deckungsraten und empirischem Standardfehler, zeigten Ridge Regression, Lasso und der Random Forest Algorithmus. Aus den Ergebnissen dieser Studie kann abgeleitet werden, dass die zuletzt genannten Methoden in zukünftige LiDAR unterstützten Waldinventuren Berücksichtigung finden sollten.

La tesis consta de dos partes. En la primera parte se analiza la relación entre las fricciones en los flujos de información que llegan a la empresa y la persistencia del patrón de la inflación. En particular, se presenta un nuevo estimador por el modelo de Makiw y Reis (2002) "Sticky Information Phillips Curve", y se aplica usando datos trimestrales de EE.UU. El resultado principal es que el modelo tan solo puede explicar la persistencia de la inflación asumiendo que la variancia de la inflación sea mucho mas grande de la que observamos o, equivalentemente, que el modelo no puede explicar conjuntamente la variancia y la persistencia de la inflación.En la segunda parte se presentan nuevas evidencias sobre la publicidad agregada en EE.UU. y se estudian los efectos de la publicidad en la economía usando un modelo dinámico estocástico de equilibrio general. En particular, el capitulo 2 se enfoca en las relaciones de corto plazo entre las mas comunes variables macroeconómicas - consumo agregado, producto interno bruto, totalidad de horas trabajadas en la economía - y la publicidad agregada, con particular atención a la relación de causalidad entre publicidad y consumo. En cambio, el capitulo 3 se enfoca sobre las relaciones de largo plazo, enseñando como la publicidad agregada afecte el nivel de trabajo de la economía. A través del modelo presentado en el capitulo 2, se demuestra que un mayor nivel de publicidad implica un mayor números de oras trabajadas asociadas con un menor nivel de bienestar por los consumidores. / This thesis is organized in two parts. In the first one, I seek to understand the relationship between frictions in information flows among firms and inflation persistence. To this end, I present a novel estimator for the Sticky Information Phillips Curve (Mankiw and Reis, 2002), and I use it to estimate this model with U.S. postwar data. The main result is that the Sticky Information Phillips Curve can match inflation persistence only at the cost of mispredicting inflation variance. I conclude that the Sticky Information Phillips Curve is a valid model to explain inflation persistence but not an overall valid theory of inflation. The second part presents new evidence about aggregate advertising expenditures in U.S., and analyzes the effect of advertising in the aggregate economy by the mean of a dynamic stochastic general equilibrium model. Chapter 2 focuses on the short run impact of advertising on the aggregate dynamics, and shows that an increase in aggregate advertising significantly increases the aggregate consumption. Chapter 3 focuses on the long run effects of advertising on the labor supply, showing that in economies where aggregate advertising is higher, agents supply more hours of works and are generally worse off in terms of welfare.

Este trabalho apresenta uma estratégia para a estimativa de velocidade do motor de indução trifásico baseada em redes neurais artificiais utilizando medidas de variáveis primárias como tensão e corrente. O uso de motores de indução trifásicos é uma constante em diversos setores industriais e de grande importância no cenário energético nacional. A maioria das metodologias de controle, acionamento e dimensionamento destes motores é fundamentada nas medidas de velocidade no eixo. Entretanto, a medida direta da velocidade compromete o sistema de controle e acionamento diminuindo sua robustez e aumentando o custo de implementação. Resultados de simulação e de ensaios experimentais para validação da proposta são também apresentados. / This work presents an approach to estimate speed in induction motors based on artificial neural networks and using measurement of primary variables like voltage and current. The use of induction motors is very common in many industrial sectors and plays an important role in the national energetic scene. The methodologies used in control, start up and dimensioning of these motors are based on measure of the speed variable. However, the direct measure of this variable compromises the system control and start up of the machine, reducing its robustness and increasing the implementation costs. Simulation results and experimental data are presented to validate the proposed approach.

On étudie un système de particules en interactions. Deux types de processus sont utilisés pour modéliser le système. Tout d'abord des processus de Hawkes. On propose deux modèles pour lesquels on obtient l'existence et l'unicité d'une version stationnaire, ainsi qu'une construction graphique de la mesure stationnaire à l'aide d'une décomposition de type Kalikow et d'un algorithme de simulation parfaite.Le deuxième type de processus utilisés est un processus de Markov déterministe par morceaux (PDMP). On montre l'ergodicité de ce processus et propose un estimateur à noyau pour la fonction de taux de saut possédant une vitesse de convergence optimale dans L². / We work on interacting particles systems. Two different types of processes are studied. A first model using Hawkes processes, for which we state existence and uniqueness of a stationnary version. We also propose a graphical construction of the stationnary measure by the mean of a Kalikow-type decomposition and a perfect simulation algorithm.The second model deals with Piecewise deterministic Markov processes (PDMP). We state ergodicity and propose a Kernel estimator for the jump rate function having an optimal speed of convergence in L².

Submitted by Valquíria Barbieri (kikibarbi@hotmail.com) on 2018-05-04T22:14:33Z No. of bitstreams: 1 DISS_2014_Evaldo Oestreich Filho.pdf: 2713813 bytes, checksum: bf84148c7524af203433132e7a61a4b8 (MD5) / Approved for entry into archive by Jordan (jordanbiblio@gmail.com) on 2018-05-16T16:43:42Z (GMT) No. of bitstreams: 1 DISS_2014_Evaldo Oestreich Filho.pdf: 2713813 bytes, checksum: bf84148c7524af203433132e7a61a4b8 (MD5) / Made available in DSpace on 2018-05-16T16:43:42Z (GMT). No. of bitstreams: 1 DISS_2014_Evaldo Oestreich Filho.pdf: 2713813 bytes, checksum: bf84148c7524af203433132e7a61a4b8 (MD5) Previous issue date: 2014-02-20 / CAPES / O estudo foi desenvolvido no estado de Mato Grosso, em dois locais, sendo o primeiro localizado no município de Cuiabá, Mato Grosso, Brasil, denominada Área 1 e o segundo localizado no município de Chapada dos Guimarães denominado Área 2. O presente trabalho teve como objetivos caracterizar o estrato arbóreo das comunidades de cerrado estudadas; quanto a riqueza, a florística, a estrutura fitossociológica e diversidade; determinar a similaridade entre cerrados fragmentos estudados e compará-los quanto à florística, estrutura fitossociológica e diversidade. Para este estudo foram alocadas 30 parcelas na área 1 e 32 parcelas na área 2, todas com tamanhos 20 m x 20 m (400 m²), totalizando 12.000 m² e 12.800 m², respectivamente nas Áreas 1 e 2. A suficiência de amostragem foi obtida com base na análise da curva do coletor por meio do estimador não-paramétrico Jackknife, a diversidade através do índice de Shannon, a equabilidade através do índice de Simpson e a similaridade das áreas foi calculada por meio do índice de Sorensen. As espécies foram organizadas de acordo com as famílias reconhecidas pelo Angiosperm Phylogeny Group III. Foram encontradas nas áreas 1 e 2, um total de 3139 indivíduos arbóreos distribuídos em 82 espécies entre indivíduos com DAB ≥ 5 cm, sendo 8 espécies identificadas somente em nível de gênero. Essas espécies distribuem-se entre 57 gêneros, 31 famílias botânicas. As famílias mais bem representadas em número de espécies foram: Fabaceae, Myrtaceae, Vochysiaceae, Apocynaceae, Annonaceae e Bignoniaceae. As espécies Qualea parviflora e Kielmeyera coriacea estiveram presentes em todas as parcelas levantadas no fragmento de cerrado estudado no município de Cuiabá, e, portanto, obtiveram frequência absoluta de 100%. As espécies Couepia grandiflora, Davilla elliptica e Qualea grandiflora estiveram presentes em 93,75% de todas as parcelas levantadas na área pertencente à Chapada dos Guimarães. A diversidade e a equabilidade, respectivamente, pelo índice de Shannon e de Simpson, foram: 3,34 e 0,9520 na área 1; 3,56 e 0,9559 na área 2. A similaridade entre as áreas estudadas foi de 42% pelo índice de Sorensen. Os resultados encontrados confirmaram que as famílias Fabaceae, Myrtaceae e Vochysiaceae são as mais representativas floristicamente nos cerrados do Brasil Central. / The study was conducted in the state of Mato Grosso, in two places, the first located in the the municipality of Cuiaba , Mato Grosso, Brazil and called Area 1 and the second located in the municipality of Chapada dos Guimarães called Area 2. The objective of this study was to characterize the arboreal stratum of the communities of cerrado, as richness, floristic, phytosociological structure and diversity; determine the similarity between cerrado fragments studied and compare them with respect to floristic, phytosociological structure and diversity. For this study, 30 plots were allocated in Area 1 and 32 plots in Area 2, all of them with size 20 m x 20 m (400 m²), with total 12,000 m² and 12,800 m², respectively in areas 1 and 2. The sampling adequacy was obtained based on the analysis of the curve through nonparametric Jackknife estimator, the diversity was calculated using the Shannon index, the equability across the Simpson index and the similarity of the areas was calculated using the Sorensen index. The species were arranged according to families recognized by the Angiosperm Phylogeny Group III. Were found a total of 3139 individual trees belonging to 82 species among individuals with the diameter average the base (DAB) ≥ 5 cm, with only 8 species identified at genus. These species is distributed among 57 genera, 31 botanical families. The families that had the best representations in number of species were: Fabaceae, Myrtaceae, Vochysiaceae, Apocynaceae, Annonaceae and Bignoniaceae. The species Qualea parviflora and Kielmeyera coriacea were present in all plots raised in cerrado fragment in Cuiabá, so had absolute frequency of 100%. The species Couepia grandiflora, Davilla elliptica and Qualea grandiflora were present in 93.75% of all parcels raised in Chapada of Guimarães. The diversity and the equability, respectively, by Shannon and Simpson indexes, were: 3.34 and 0.9520 in Area 1; 3.56 and 0.9559 in Area 2. The similarity between study areas showed 42% similarity by Sorensen index. The results confirmed that the Fabaceae, Myrtaceae and Vochysiaceae families are the most representative flora in cerrado of central Brazil.

Made available in DSpace on 2014-12-17T14:56:03Z (GMT). No. of bitstreams: 1 OsmarADJ.pdf: 1159660 bytes, checksum: 65307a903dfe1a1f71297194d1c7e2a5 (MD5) Previous issue date: 2004-12-22 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / This dissertation presents a new proposal for the Direction of Arrival (DOA) detection problem for more than one signal inciding simultaneously on an antennas array with linear or planar geometry by using intelligent algorithms. The DOA estimator is developed by using techniques of Conventional Beam-forming (CBF), Blind Source Separation (BSS), and the neural estimator MRBF (Modular Structure of Radial Basis Functions). The developed MRBF estimator has its capacity extended due to the interaction with the BSS technique. The BSS makes an estimation of the steering vectors of the multiple plane waves that reach the array in the same frequency, that means, obtains to separate mixed signals without information a priori. The technique developed in this work makes possible to identify the multiple sources directions and to identify and to exclude interference sources / Esta disserta??o apresenta uma nova proposta para os problemas de detec??o de dire??o de chegada para mais de um sinal incidindo simultaneamente sobre um arranjo de antenas de geometria planar ou linear empregando algoritmos inteligentes. O estimador de DOA ? desenvolvido utilizando as t?cnicas de Conforma??o de Feixes Digital Convencional (CBF - Conventional Beamforming), de Separa??o Cega de Fontes (BSS {Blind Source Separation) e o estimador neural MRBF (Modular Structure of Radial Basis Functions). O estimador MRBF desenvolvido tem sua capacidade ampliada gra?as ?a intera??o com a t?cnica BSS, a qual faz uma estima??o dos vetores de guiamento das m?ltiplas ondas planas que alcan?am o arranjo na mesma freq??ncia, isto ?, consegue separar sinais misturados sem informa??es a priori. A t?cnica desenvolvida neste trabalho possibilita identificar a dire??o de m?ltiplas fontes e identificar e excluir as fontes de interfer?ncia