Výsledky vyhledávání - "valk, Marcio"

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A three-step approach to production frontier estimation and the Matsuoka's distribution

Autor: Matsuoka, Danilo Hiroshi, Pumi, Guilherme, Torrent, Hudson da Silva, valk, Marcio

In this work, we introduce a three-step semiparametric methodology for the estimation of production frontiers. We consider a model inspired by the well-known Cobb-Douglas production function, wherein input factors operate multiplicatively within the

Externí odkaz: http://arxiv.org/abs/2311.06086

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Fault detection and diagnosis of batch process using dynamic ARMA-based control charts

Autor: de Oliveira, Batista Nunes, Valk, Marcio, Filho, Danilo Marcondes

A wide range of approaches for batch processes monitoring can be found in the literature. This kind of process generates a very peculiar data structure, in which successive measurements of many process variables in each batch run are available. Tradi

Externí odkaz: http://arxiv.org/abs/2109.00952

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Clustering inference in multiple groups

Autor: Bello, Debora Zava, Valk, Marcio, Cybis, Gabriela Bettella

Inference in clustering is paramount to uncovering inherent group structure in data. Clustering methods which assess statistical significance have recently drawn attention owing to their importance for the identification of patterns in high dimension

Externí odkaz: http://arxiv.org/abs/2106.09115

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Akademický článek

A model-free-based control chart for batch process using U-statistics

Autor: Cintra, Renan Faraon, Valk, Marcio, Marcondes Filho, Danilo

Publikováno v: In Journal of Process Control December 2023 132

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Beta Autoregressive Fractionally Integrated Moving Average Models

Autor: Pumi, Guilherme, Valk, Marcio, Bisognin, Cleber, Bayer, Fábio Mariano, Prass, Taiane Schaedler

In this work we introduce the class of beta autoregressive fractionally integrated moving average models for continuous random variables taking values in the continuous unit interval $(0,1)$. The proposed model accommodates a set of regressors and a

Externí odkaz: http://arxiv.org/abs/1807.10338

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U-statistical inference for hierarchical clustering

Autor: Valk, Marcio, Cybis, Gabriela Bettella

Clustering methods are a valuable tool for the identification of patterns in high dimensional data with applications in many scientific problems. However, quantifying uncertainty in clustering is a challenging problem, particularly when dealing with

Externí odkaz: http://arxiv.org/abs/1805.12179

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Clustering and Classification of Genetic Data Through U-Statistics

Autor: Cybis, Gabriela Bettella, Valk, Marcio, Lopes, Silvia Regina Costa

Genetic data are frequently categorical and have complex dependence structures that are not always well understood. For this reason, clustering and classification based on genetic data, while highly relevant, are challenging statistical problems. Her

Externí odkaz: http://arxiv.org/abs/1606.03376

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Dissertation/ Thesis

O uso de quase U-estatísticas para séries temporais uni e multivaridas

Autor: Valk, Marcio

Publikováno v: Repositório Institucional da UnicampUniversidade Estadual de CampinasUNICAMP.

Orientador: Aluísio de Souza Pinheiro
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática Estatítica e Computação Científica
Made available in DSpace on 2018-08-17T14:57:09Z (GMT). No. of bitstreams: 1 Valk_M

Externí odkaz: http://repositorio.unicamp.br/jspui/handle/REPOSIP/307526

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