Habilitationsschrift--Breslau. / "Aus den Sitzungsberichten der Kaiserl. Akademie der wissenschaften in Wien. Mathem.-naturw.klasse; bd. CXVIII, abt. IIa, Dezember 1909." Lebenslauf.

Habilitationsschrift--Breslau. / "Aus den Sitzungsberichten der Kaiserl. Akademie der wissenschaften in Wien. Mathem.-naturw.klasse; bd. CXVIII, abt. IIa, Dezember 1909." Lebenslauf.

Thesis (Ph. D.)--University of Wisconsin, 1966. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Th.--Sci.--Toulouse 3, 1981. N°: 969.

No description available.

Made available in DSpace on 2014-06-12T18:05:13Z (GMT). No. of bitstreams: 2 arquivo7239_1.pdf: 1392716 bytes, checksum: a11779fe60e360c2162def3f63a2238e (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2005 / Modelagem de dados restritos ao intervalo (0,1) é muito comum na prática. Para modelar dados desta natureza podemos fazer uso da distribuição beta. Contudo, quando o interesse é estudar conjuntamente variáveis que estão compreendidas no intervalo (0,1) e trabalhar com modelos multivariados, uma distribuição útil é a Dirichlet, que é uma generalização da distribuição beta. Nesta dissertação avaliamos a influência local através da curvatura normal conforme para dados correspondentes a variáveis independentes e identicamente distribuídas (i.i.d.) segundo a distribuição Dirichlet. A metodologia da curvatura normal conforme foi proposta por Poon & Poon (1999) para avaliar medidas de influência segundo pequenas perturbações nos dados ou no modelo é considerada no contexto da distribuição Dirichlet. Consideramos dois esquemas de perturbação, um em que uma das componentes é modificada através das formas aditiva e multiplicativa e outro em que perturbamos a log-verossimilhança de forma multiplicativa. Após analisarmos as observações influentes através de tais medidas, comparamos as estimativas dos parâmetros da distribuição Dirichlet quando todas as observações estão presentes nos dados com as estimativas desses parâmetros ao retirarmos uma observação influente com o intuito de verificar o impacto causado nas estimativas

Orientador : Ubiratan D'Ambrosio / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-07-14T03:20:07Z (GMT). No. of bitstreams: 1 Bassanezi_RodneyCarlos_D.pdf: 623120 bytes, checksum: 7fdb59cf4bdea377eab4097acc09865b (MD5) Previous issue date: 1976 / Resumo: Não informado. / Abstract: Not informed. / Doutorado / Doutor em Matemática

Orientador: Syairo Guedes de Figueiredo / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Científica / Made available in DSpace on 2018-07-19T14:17:47Z (GMT). No. of bitstreams: 1 Carvalho_AnaMarciaFernandesTuccide_M.pdf: 1229895 bytes, checksum: 02725b0601aa6469d7c8ea2206e11128 (MD5) Previous issue date: 1994 / Resumo: Não informado. / Abstract: Not informed. / Mestrado / Mestre em Matemática

In this paper we study the uniqueness of positive solutions as well as the non existence of sign changing solutions for Dirichlet problems of the form $$\eqalign{\Delta u + g(\lambda,\ u) &= 0\quad\rm in\ \Omega,\cr u &= 0\quad\rm on\ \partial\Omega,}$$where $\Delta$ is the Laplace operator, $\Omega$ is a region in $\IR\sp{N}$, and $\lambda>0$ is a real parameter. For the particular function $g(\lambda,\ u)=\vert u\vert\sp{p}u+\lambda$, where $p={4\over N-2}$, and $\Omega$ is the unit ball in $\IR\sp{N}$ for $N\ge3$, we show that there are no sign changing solutions for small $\lambda$ and also we show that there are no large sign changing solutions for $\lambda$ in a compact set. We also prove uniqueness of positive solutions for $\lambda$ large when $g(\lambda,\ u)=\lambda f(u)$, where f is an increasing, sublinear, concave function with f(0) $<$ 0, and the exterior boundary of $\Omega$ is convex. In establishing our results we use a number of methods from non-linear functional analysis such as rescaling arguments, methods of order, estimation near the boundary, and moving plane arguments.

There exist many data classification methods and algorithms; however the importance of them has not diminished. The data and information quantities increase as well as the diversity of information, so the question is how to reliably process the data. Various considerations emerge concerning what method to choose or which of them fits for data best, i.e. which of them would classify data most accurately and reliably. This work presents a classification method based on the statistics of Dirichlet mixtures. Dirichlet mixture combines more than one Dirichlet densities that are described by the same set of parameters but with different values of them. Such a Dirichlet mixture becomes sensitive to recognize differently distributed variables (data) and hence, utilization of the Dirichlet mixtures in classification can provide a powerful tool for classification of data of any kind. This thesis proposes a method describing how Dirichlet mixtures can be utilized for classification of data of any kind. With regard to this, a Dirichlet mixtures classifier is designed to classify data of any type and with any range of values. The designed classifier classifies numerical data as well as symbolic ones. The Dirichlet mixtures classifier is implemented in two ways: The first one concerns the classifier as the end-product for a user and the second one relates to a compiled library of classification routines. Using the Dirichlet mixtures classifier as the product, the user can classify data and... [to full text]