Made available in DSpace on 2014-12-17T14:12:03Z (GMT). No. of bitstreams: 1 AlexandreBL_TESE.pdf: 4327655 bytes, checksum: 57b0b9f8e05c550b153e77bf0aa25eff (MD5) Previous issue date: 2014-03-26 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / The increase in ultraviolet radiation (UV) at surface, the high incidence of non-melanoma skin cancer (NMSC) in coast of Northeast of Brazil (NEB) and reduction of total ozone were the motivation for the present study. The overall objective was to identify and understand the variability of UV or Index Ultraviolet Radiation (UV Index) in the capitals of the east coast of the NEB and adjust stochastic models to time series of UV index aiming make predictions (interpolations) and forecasts / projections (extrapolations) followed by trend analysis. The methodology consisted of applying multivariate analysis (principal component analysis and cluster analysis), Predictive Mean Matching method for filling gaps in the data, autoregressive distributed lag (ADL) and Mann-Kendal. The modeling via the ADL consisted of parameter estimation, diagnostics, residuals analysis and evaluation of the quality of the predictions and forecasts via mean squared error and Pearson correlation coefficient. The research results indicated that the annual variability of UV in the capital of Rio Grande do Norte (Natal) has a feature in the months of September and October that consisting of a stabilization / reduction of UV index because of the greater annual concentration total ozone. The increased amount of aerosol during this period contributes in lesser intensity for this event. The increased amount of aerosol during this period contributes in lesser intensity for this event. The application of cluster analysis on the east coast of the NEB showed that this event also occurs in the capitals of Paraiba (Jo?o Pessoa) and Pernambuco (Recife). Extreme events of UV in NEB were analyzed from the city of Natal and were associated with absence of cloud cover and levels below the annual average of total ozone and did not occurring in the entire region because of the uneven spatial distribution of these variables. The ADL (4, 1) model, adjusted with data of the UV index and total ozone to period 2001-2012 made a the projection / extrapolation for the next 30 years (2013-2043) indicating in end of that period an increase to the UV index of one unit (approximately), case total ozone maintain the downward trend observed in study period / A eleva??o da radia??o ultravioleta (UV), a alta incid?ncia de c?ncer de pele n?o melanoma (CPNM) no Nordeste do Brasil (NEB) e a redu??o da coluna total de oz?nio foram os motivadores do presente estudo. O objetivo desta investiga??o ? identificar e compreender a variabilidade da UV e do ?ndice de Radia??o Ultravioleta (?ndice UV) nas capitais da costa leste do NEB e ajustar modelos estoc?sticos ?s s?ries temporais do ?ndice UV visando realizar predi??es (interpola??es) e previs?es/proje??es (extrapola??es) seguido de an?lise de tend?ncia. A metodologia consistiu da aplica??o da an?lise multivariada (an?lise de componentes principais e an?lise de agrupamentos), m?todo Predictive Mean Matching (PMM) para preenchimento de falhas nos dados, modelo autoregressivo de defasagens distribu?das ou Autoregressive Distributed Lag (ADL) e teste Mann-Kendal. A modelagem via ADL ocorreu atrav?s da estima??o de par?metros, diagn?stico, an?lise de res?duos e avalia??o da qualidade das predi??es/previs?es via erro quadr?tico m?dio e coeficiente de correla??o de Pearson. Os resultados da investiga??o indicaram que a variabilidade anual da UV na capital do Rio Grande do Norte (Natal) possui uma caracter?stica nos meses de setembro e outubro que consiste em uma estabiliza??o/redu??o do ?ndice UV em raz?o da maior concentra??o anual de oz?nio total. A maior quantidade de aeross?is neste per?odo contribui em menor intensidade para este evento. A aplica??o da an?lise de agrupamento (cluster) na costa leste do NEB mostrou que este evento tamb?m ocorre nas capitais da Para?ba (Jo?o Pessoa) e Pernambuco (Recife). Os eventos extremos da UV do NEB foram analisados a partir da cidade de Natal e estavam associados ? falta de cobertura de nuvens e n?veis abaixo da m?dia anual de oz?nio total e n?o ocorriam na totalidade da regi?o em fun??o da distribui??o espacial desigual dessas vari?veis. O modelo ADL (4, 1), ajustado com dados do ?ndice UV e oz?nio total para o per?odo de 2001 a 2012, realizou a proje??o/extrapola??o para os pr?ximos 30 anos (2013-2043) indicando ao fim deste per?odo eleva??o de aproximadamente uma unidade do ?ndice UV, caso o oz?nio total mantenha a tend?ncia de queda verificada no per?odo de estudo

A statistician's job is to produce statistical models. When these models are precise and unbiased, we can relate them to new data appropriately. However, when data sets have missing values, assumptions to statistical methods are violated and produce biased results. The statistician's objective is to implement methods that produce unbiased and accurate results. Research in missing data is becoming popular as modern methods that produce unbiased and accurate results are emerging, such as MICE in R, a statistical software. Using real data, we compare four common imputation methods, in the MICE package in R, at different levels of missingness. The results were compared in terms of the regression coefficients and adjusted R^2 values using the complete data set. The CART and PMM methods consistently performed better than the OTF and RF methods. The procedures were repeated on a second sample of real data and the same conclusions were drawn.

The objective of this thesis is to evaluate different methods of dealing with missing values in data analysis. The thesis is divided into three major chapters. The first chapter summarizes the theoretical literature on missing data and focuses on missing data mechanisms in particular. The second chapter introduces traditional methods for addressing missing data in sociological research. The third chapter assesses the performance of these methods by analyzing simulated data sets for two variables (income, IQ). For practical analysis (chapter 3), we simulated missing data according to three different mechanisms (MCAR, MAR, NMAR) and varied the proportion of missing values under these mechanisms (10%, 20%, 30%). Then, we applied each of the following four methods of addressing missing values: complete-case analysis, arithmetic mean imputation, regression imputation, and stochastic regression imputation. In order to evaluate the performance of each of these methods we performed correlation and regression analyses for each experimental condition. The results of these simulations are largely in agreement with existing theoretical literature on the subject of missing data. In the case of NMAR, all solution methods provided biased parameter estimates. In the case of MCAR, only complete-case analysis and...