DSpace Coleção:
https://repositorio.ufrn.br/jspui/handle/123456789/12035
2020-07-08T14:24:26ZGráficos de controle para o monitoramento de dados simétricos e log-simétricos
https://repositorio.ufrn.br/jspui/handle/123456789/28930
Título: Gráficos de controle para o monitoramento de dados simétricos e log-simétricos
Autor(es): Sales, Lucas de Oliveira Ferreira de
Abstract: Since the industrial revolution until to the present day it is in the industry’s interest to
monitor the quality of their products, aiming at good quality product, good operation on
the production line and a profitable production. In this context, control charts are the
main tools used for monitoring a particular quality characteristic. Usually the monitored
characteristic is the process mean and the most used control chart for such monitoring
are: X of Shewhart, CUSUM and EWMA, which are based on two assumptions: independence between the monitored samples and that the monitored variable follows a normal
distribution. However, breaking any of these assumptions implies in a poor control chart
performance. Considering this, the present work proposes a control chart, for the monitoring of the mean, based on the bootstrap method for data that follows a distribution
that belongs to the symmetric class of distributions. In addition, a monitoring method
was proposed for the monitoring of the median (which in case of asymmetric data is
more informative than the mean) for data that belong to the log-symmetric class of distributions, based on the empirical distribution of three new median estimators proposed
by Balakrishnan et al. (2017). Additionally, simulation studies were performed for both
proposed methods, in order to evaluate the in-control and the out-control average run
length (ARL), to evaluate the behavior of the control limits and to compare the proposed
method with the traditional methods for each situation. As result, the simulation study
indicates that the proposed approaches presents better ARL0 than the usual methods.
Regarding to the power of detection, the proposed methods present good performance,
being comparable to traditional methods, but with the advantage of better ARL0. In addition, the work presents an application for each of the two proposed methods in order
to illustrate their applicability in a real situation.2020-02-19T00:00:00ZModelo de regressão beta modal
https://repositorio.ufrn.br/jspui/handle/123456789/28929
Título: Modelo de regressão beta modal
Autor(es): Silva, Erika Rayanne Fernandes da
Abstract: The beta regression model is a class of models used for continuous response variables
restricted to the interval (0,1), such as rates and proportions. Ferrari and Cribari-Neto
(2004) proposed a beta regression model that incorporates covariates in the mean of the
distribution using a generic link function. However, for studies which response variable
has asymmetry and / or discrepant values, this model may not be the most appropriated. A more appropriated measure of central tendency in this kind of situation is the
mode of distribution because of its robustness to outliers and its easy interpretation in
cases of asymmetry. Zhou and Huang (2019) proposed a parameterization for the beta
distribution in terms of the mode and a precision parameter. Assuming that the response
variable follows this distribution, Zhou and Huang (2019) proposed a regression model
for continuous data in the interval (0,1), in order to be more robust to outliers. In this
work, we present a more complete study of this model properties and performance as well
as a comparison between this model and the model proposed by Ferrari and Cribari-Neto
(2004). We developed simulation studies to evaluate the maximum likelihood estimates in
cases of asymmetry and the sensitivity to outliers when come perturbation patterns are
imposed. Furthermore, we proposed and evaluated three residuals to this class of models.
Our simulation studies suggest that the model developed to the mode has a good performance on symmetrical and asymmetrical data and in most scenarios it performs better
in the presence of outliers than the beta regression model that considers the mean. In
addition, we present two applications to real dataset and a t comparison of the models
that consider the mean and the mode.2020-02-18T00:00:00ZMetrizabilidade de topologias e distâncias generalizadas
https://repositorio.ufrn.br/jspui/handle/123456789/28928
Título: Metrizabilidade de topologias e distâncias generalizadas
Autor(es): Nascimento, Bismark Gonçalves do
Abstract: In this work, we present a study on the metrizability of topologies presenting the necessary
conditions for a topology to be metrizable, i.e., it can be constructed starting from a
metric originating from open balls. In addition, several interesting examples of topologies
are presented to show that many of the presented are only necessary. Moreover, the
Nagata-Smirnov Bing theorem is also mentioned, which presents necessary and sufficient
conditions for a topology to be metrizable. In addition, we present a generalization of
the concept of metric, which is called V-valued i-metric. Through this generalization we
define the concepts of V-valued i-quasi-metric, V-valued i-pseudometric and V-valued iquasipseudometric and it is proved that every topology is i-quasi-pseudometrizable. Based
on the theory of interval math an interval metric is constructed which is a particular case
of i-metric. This interval metric also generates a topology and we assess whether this
topology is metrizable.2020-03-02T00:00:00ZDengue em Natal/RN: uma análise do período 2000-2016 via séries temporais
https://repositorio.ufrn.br/jspui/handle/123456789/28541
Título: Dengue em Natal/RN: uma análise do período 2000-2016 via séries temporais
Autor(es): Barros, Talita Viviane Siqueira de
Abstract: Dengue fever is an infectious disease transmitted by the Aedes aegypti mosquito. This
vector also transmits the chikungunya, zika and yellow fever. In 2019, the World Health
Organization (WHO) has established the fight against dengue as one of the ten priorities
for this year. It is estimated that almost half of the world’s population is at risk of dengue
infection. Based on the above, this study aims to analyze data on reported cases of dengue
fever between 2000 and 2016, obtained from the Center for Zoonoses Control (CCZ) in the
city of Natal/RN, through time series. In Natal/RN since 2000 dengue outbreaks occur,
implying the existence of possible atypical observations (denoted in this paper by outliers)
in the historical series. In addition, an outbreak of zika occurred in 2015 and because of
a similar symptoms, cases may have been reported as dengue. Therefore, we search for a
model that considers information of possible pattern changes and existence of outliers by
intervention analysis. The exponential smoothing methods simple, Holt and HoltWinters
were also used, as well as the ARIMAX model with exogenous climatic variables. Models
are compared using root mean square error (rMSE) and mean absolute error (MAE) of
forecasts for the first 37 weeks of 2017. The GARCH model was used to estimate the
volatility of the series.2019-11-29T00:00:00Z