A distribuição gama generalizada (GG) possui, como casos particulares, distribuição Weibull, log-normal, gama, qui-quadrado, entre outras. Por essa razão, ela e considerada uma distribuição exvel no ajuste dos dados. A ideia de Cordeiro e Castro (2011) foi utilizada para o desenvolvimento de duas novas distribuições de probabilidade a partir da distribuição GG. Uma delas e denominada de Kumaraswamy gama generalizada (KumGG) e possui cinco parâmetros; a outra distribuição e uma modificação de um dos parmetros de forma da distribuição KumGG e foi denominada de distribuição Kumaraswamy gama generalizada estendida (KumGGE). Desenvolveu-se o modelo de regressão log-Kumaraswamy gama generalizada estendida. Alem disso, a ideia de Adamidis e Loukas (1998) para modicar distribuições foi utilizada para a distribuição GG; essa nova distribuição foi nomeada de gama generalizada geometrica (GGG). A vantagem desses novos modelos reside na capacidade de acomodar varias formas da função risco eles tambem se mostraram uteis na discriminação de modelos. Para cada um dos modelos foram calculados os momentos, função geradora de momentos, os desvios medios, a conabilidade e a função densidade de probabilidade da estatistica de ordem. Para a estimação dos parâmetros, foram utilizados os metodos de maxima verossimilhanca e bayesiano e, finalmente, para ilustrar a aplicação das novas distribuições foram analisados alguns conjuntos de dados reais. / The generalized gamma (GG) distribution has as particular cases the Weibull, log-normal, gamma and Chi-square distributions, among others. For this reason, it is considered a exible distribution for tting data. In this paper, the idea of Cordeiro and Castro (2011) is used to develop two new probability distributions based on the GG distribution. The rst is called the generalized gamma Kumaraswamy (KumGG) and has ve parameters, while the other involves a modication of one of the shape parameters of the KumGG distribution and is called the extended generalized gamma Kumaraswamy (KumGGE). Based in these, we develop the extended generalized log-Kumaraswamy regression model. Besides this, we employ the idea regarding modifying distributions of Adamidis and Loukas (1998) for the GG distribution, calling this new distribution the geometric generalized gamma (GGG). The advantage of these new models rests in their capacity to accommodate various risk function forms. They are also useful in model discrimination. We calculate the moments, moments generating function, mean deviations, reliability and probability density function of the order statistics. To estimate the parameters we use the maximum likelihood and Bayesian methods. Finally, to illustrate the application of the new distributions, we analyze some real data sets.

Made available in DSpace on 2017-07-10T19:23:56Z (GMT). No. of bitstreams: 1 Ademir Natal Correa.pdf: 1505539 bytes, checksum: fd8e294f5766bf4043789d75eba28f1f (MD5) Previous issue date: 2007-07-16 / The objective of this study was to assess the relationship among soil physical attributes and their influences on wheat yield. For this purpose an estimating method, called State-Space Model or dynamic linear regression model, was used and compared to simple and multiple regression models of classical statistics. Experimental data were obtained at a Rhodic Ferralsol, originated from UNIOESTE Agricultural Engineering Experimental Nucleus Cascavel Campus, in an area where wheat was grown. In this area, 3 equally spaced transects, with 97 sampling points, 3.0 meters away from each other, were delimited. The State-Space approach was used to assess wheat yield estimate on position i, influenced by wheat yield, bulk density, soil compaction degree and soil resistance to penetration on position i-1 in different combination between data series of these variables. Applying the State-Space approach, all the response variables presented significant correlation with the dependent variable: soil resistance to penetration was the attribute with the best correlation, presenting R2 coefficient equal to 0.849. The other attributes had R2 coefficient of around 0.800. Comparing to conventional static models, soil resistance to penetration attribute had R2 coefficient equal to 0.102. The other attributes had R2 coefficient equal or less than 0.087, in conventional regression. Utilizing the State-Space approach, the two combinations that indicated the best results were: 1) between wheat yield and soil resistance to penetration that showed the best estimate to wheat yield with R2 coefficient equal to 0.849, while the same combination in conventional regression presented R2 equal to 0.102; 2) between wheat yield, soil compaction degree and soil resistance to penetration, with R2 coefficient equal to 0.836, while the same combination in classical regression presented R2 equal to 0.217. Thus, it is possible to show the advantage of the State-Space approach in relation to other more conventional regression methods for estimating and forecasting in soil-plant system relationship. / Este trabalho foi realizado com o objetivo de estudar o relacionamento entre os atributos físicos do solo e a influência destes na produtividade de trigo. Para isso, utilizou-se o método de estimação chamado de Modelo de Espaço de Estados ou modelo de regressão linear dinâmico, comparando-o aos modelos de regressão simples e múltipla da estatística clássica. Os dados experimentais foram obtidos em um Latossolo Vermelho-Escuro pertencente ao Núcleo Experimental de Engenharia Agrícola da Universidade Estadual do Oeste do Paraná Campus de Cascavel, em uma área cultivada com trigo. Foram demarcadas 3 transeções com 97 pontos de amostragem espaçados de 3 m entre si. A abordagem de Espaço de Estados foi usada para avaliar a estimativa da produtividade do trigo na posição i, influenciada por medidas da produtividade do trigo, da densidade do solo, do grau de compactação do solo e da resistência do solo à penetração na posição i-1, em diferentes combinações entre as séries de dados dessas variáveis. Com a aplicação da abordagem de Espaço de Estados, todas as variáveis explicativas utilizadas apresentaram correlação significativa com a variável dependente: a resistência do solo à penetração foi o atributo com a melhor correlação, apresentando o coeficiente de ajuste R2 igual a 0,849. Os demais atributos tiveram os coeficientes R2 em torno de 0,800. Comparando-se com os modelos estáticos convencionais, o atributo resistência do solo à penetração teve o coeficiente de ajuste R2 igual a 0,102 e os demais atributos tiveram os seus coeficientes R2 abaixo de 0,087, na regressão convencional. Utilizando a metodologia de Espaço de Estados, as duas combinações que indicaram os melhores resultados foram a combinação entre produtividade do trigo e resistência do solo à penetração, que apresentou a melhor estimativa para produtividade do trigo, com coeficiente R2 igual a 0,849. A mesma combinação na regressão convencional resultou em R2 igual a 0,102. A segunda melhor combinação ocorreu entre os atributos: produtividade do trigo, grau de compactação do solo e resistência do solo à penetração, com R2 igual a 0,836, sendo que a mesma combinação na regressão clássica teve o coeficiente R2 igual a 0,217. Com isso é possível mostrar-se a vantagem da abordagem de Espaço de Estados em relação a outros métodos de estimativa e previsão para o relacionamento no sistema solo-planta.

Este trabalho é um estudo ecológico descritivo sobre a leishmaniose tegumentar americana (LTA) na região do Vale do Ribeira paulista (composto por 23 municípios), que teve como objetivo correlacionar a incidência da doença com fatores determinantes ambientais e sociais. O trabalho se refere ao período de 1998 a 2006 o qual foi divido em três triênios, o primeiro de 1998 a 2000, o segundo de 2001 a 2003 e o terceiro de 2004 a 2006. Os coeficientes de incidência da LTA foram calculados para estes períodos (Coefmtr1, Coefmtr2 e Coefmtr3) segundo Szklo. Essa divisão de triênios se deu de acordo com as características gráficas dos coeficientes de incidência da LTA no período, que demonstraram haver num primeiro período uma fase endêmica da doença, no segundo período (2001 a 2003) a análise mostra picos de incidência que caracteriza um período epidêmico acentuado. No terceiro período alguns municípios mostram picos de incidência de proporções menores que os observados no período anterior, contudo ainda característicos de fase epidêmica. Os coeficientes de incidência são as variáveis dependentes dos três modelos de regressão realizados. As variáveis independentes foram obtidas de fontes de dados secundários e são de natureza sócio-demográfica, relacionadas as condições climáticas, de natureza político-geográficas e físico-biológicas. Essas variáveis foram separadas em qualitativas e quantitativas e analisadas respectivamente por testes não paramétricos de Mann Whitney e Spearman e selecionou-se para o processo de modelagem múltipla, as variáveis com p<0,20. Houve a necessidade de três modelos diferentes para verificar se os fatores determinantes que levaram as séries a se comportar de maneira diferenciada, seriam os mesmos ou não. O que se percebe é que há uma mudança no padrão do primeiro para os dois outros períodos. O trabalho aponta para fatores sócio-demográficos como determinantes na incidência de LTA, bem como a presença do vetor / This work is an ecological descriptive study on the American cutaneous leishmaniasis (ACL) in the Ribeira Valley region of Sao Paulo (composed of 23 municipalities), which aimed to correlate the incidence of the disease with environmental and social factors. The paper refers to the period 1998 to 2006 which was divided into three years, the first from 1998 to 2000, the second from 2001 to 2003 and the third from 2004 to 2006. The rates of incidence of ACL were calculated for these periods (Coefmtr1, Coefmtr2 and Coefmtr3) Szklo seconds. This division was made in accordance with the graphics characteristics of the coefficients of incidence of ACL in the period, which has shown a period in a first stage of the disease endemic in the second period (2001 to 2003) the peak incidence analysis shows that characterizes a epidemic period strong. In the second period some municipalities show peaks of incidence of proportions lower than those observed in the previous period, yet still features the epidemic stage. The rates of incidence are dependent variables of the three regression models performed. The independent variables were obtained from sources in secondary databases, and are: in nature and socio-demographic, related climatic conditions, a political-geographical and physical and biological. These variables were separated in quality and quantity respectively and analyzed by non-parametric tests for Spearman and Mann Whitney and selected for the process of regress multiple model, the variables with p <0.20. There was a need for three different models to see if the determining factors that led to the series to behave in a different way, would be the same or not. What we understand is that there is a change in the pattern of the first to the other two periods. The study points to socio-demographic factors as determinants in the incidence of ACL and the presence of vector

This thesis analyzes the impact of the monetary policy of the Czech Republic on the Czech banking sector. It explains the monetary transmission mechanism in an inflation targeting regime and its channels: interest rates channel, asset price channel, exchange rate channel and credit channel. The aim of the thesis is to introduce and analyze channels of the Czech transmission mechanism by Correlation and Graphical Analysis of chosen time series and using Linear Regression Model. The analyses are calculated in MS Excel and Gretl.

The objective of this study is to investigate land-use changes and water quality trends within the headwaters of the Alafia River watershed. Water quality data were obtained from the Environmental Protection Commission of Hillsborough County (EPCHC). Eleven water quality parameters selected for analysis included: temperature (˚C), dissolved oxygen (DO), percent saturation of DO, conductivity, pH, total phosphorous (TP), total nitrogen (TN), ammonium, chlorophyll-a (uncorrected), fecal coliforms, and enterococci. ArcMap® & SWFWMD data were used to map EPCHC sampling stations, calculate contributing watershed size, and determine land-use changes over the course of the sampling period; 17 stations were chosen for this study. The annual average for each of the water quality parameters was calculated along with a Mann-Kendall Trend Analysis in order to determine if any of the observed trends were statistically significant. A non-parametric Kendall’s tau-b correlation and stepwise multiple linear regression tests were conducted in SPSS to determine if any statistically significant relationships between water quality data, land-use and basin size exist. The land-use results showed every basin consisted of some percentage of Low Density Residential, Cropland & Pastureland, Reservoirs, and Streams & Lake Swamps. In addition, no basin comprised of more than 20% wetlands and often it appears urbanization was at the sacrifice of agricultural lands, as opposed to wetlands. The trends in water quality showed eight of the 17 basins had at least one statistically significant trend. Analysis of the data used for this study has shown instances where water quality measurements were in violation of state standards. Changes in water quality can be statistically related to changes in land-use and basin size as both the correlation and the regression showed consistent relationships between several LULC types and water quality parameters: increases in Commercial & Services causes increased nutrients (TP and TN); Cropland & Pastureland causes decreased DO and DO% Saturation; increases in Tree Crops causes a decrease in pH; increasing Other Open Lands Rural causes a decrease in temperature; and increases in Shrub & Brushland cause decreases in conductivity and pH. As these relationships are based on the results from both analyses, it would seem that these relationships are the most reliable, and are key results of the study. These key relationships might be areas that future water resource managers may want to focus on in order to more efficiently improve or regulate water quality within headwater streams.

This thesis work regards free viewpoint TV. The main idea is that users can switch between multiple streams in order to find views of their own choice. The purpose is to provide fast switching between the streams, so that users experience less delay while view switching. In this thesis work we will discuss different video stream switching methods in detail. Then we will discuss issues related to those stream switching methods, including transmission and switching. We shall also discuss different scenarios for fast stream switching in order to make services more interactive by minimizing delays. Stream switching time varies from live to recorded events. Quality of service (QoS) is another factor to consider which can be improved by assigning priorities to the packets. We will discuss simultaneous stream transmission methods which are based on predictions and reduced quality streams for providing fast switching. We will present prediction algorithm for viewpoint prediction, propose system model for fast viewpoint switching and make evaluation of simultaneous stream transmission methods for free viewpoint TV. Finally, we draw our conclusions and propose future work. / Degree project

The demand for measuring the quality aspects and need for higher maintainability and understandability of the models are increasing within the field of software engineering and management. Among these, complex models are of special interest for designers as they are more correlated to the eventual reliability of the system and therefore are considered very important. This study presents a method for measuring the complexity of existing software models in Ericsson seeking to raise the maintainability and understandability of the software engineering project in progress. A literature survey was performed in order to find a list of all potentially useful metrics. Narrowing down the long list of metrics was carried out by interviews with designers at Ericsson. Utilizing statistical data analysis based on interviews results was the next step. Beside, workshops were used for evaluating the reliability of preliminary data analysis and an empirical formula was generated for models’ complexity prediction. Metrics such as “non-self-transitions”, “transitions per states”, and “state depth” are the most important for calculating the models’ complexity score (rank) and for these metrics threshold values were set. Challenges and experiences gained in this study demonstrated the importance of incorporating user generated feedback in the empirical complexity modeling studies

River discharge estimation is the basic hydrological information for most hydrological applications in various socioeconomic planning. Increasing the accuracy of the traditional rating curve in relation to river discharge estimation would be very valuable to hydrological applications. Suggestions have been made that the traditional power function rating curve should be divided into several segments because this is often motivated by the physical characteristics of the river. Each curve is commonly constructed by regression and each requires 3 estimated parameters. However stage-discharge data is often scarce, and this scarcity could lead to overparametrization and deterioration of accuracy. By constructing many unsegmented and segmented rating curves accounting for measurement uncertainty, the models can be validated, it can be determined if segmented rating curves suffers from overparametrization. The results showed that two-segmented rating curves did not yield better fits to data, and nor did it generate larger errors than unsegmented rating curves in extrapolation. Segmentation only reduced errors in low flow interpolation, when there is a clear segmentation.  It could also be concluded that unsegmented rating curves were slightly more robust when extrapolating. The biggest impact on rating curve errors was shown not to be determined by segmentation, but rather much more dependent on the amount of discharge measurement uncertainty or choice of regression method. With a mean discharge uncertainty of ±5 %, the errors from in high flow was 60 % in interpolation and 35 % in extrapolation. For low flows, the interpolation errors were around 95 % end extrapolation error estimation was 250 %. Conclusions could also be made that the relative errors from rating curves increased with lower discharges. Other important regression factors, such as heteroscedasticity, sometimes showed to have substantial impact on rating curve regressions, generally reduced from 59 % occurrence in unsegmented rating curves to 14-15 % in segmented rating curves. / Uppskattning av vattenflöden i vattendrag är den grundläggande informationen för de flesta hydrologiska applikationer vid olika typer av socioekonomisk planering. Att förbättra noggrannheten i avbördningskurvor då vattenflödet uppskattas vid en mätstation skulle vara värdefullt för de flesta tillämpningar där vattenflöden används. Tidigare studier har föreslagit att avbördningskurvor borde delas upp i flera segment, eftersom vattendrag inte sällan har olika segment med olika fysikaliska karaktärer. Varje segment kräver dock att 2-3 regressionsparametrar bestäms, men flödesmätningar vid olika vattennivåer är ofta få, och knappheten kan göra att en utökad modell blir överparametriserad och än mer osäker.   Genom att konstruera många avbördningskurvor, segmenterade och osegmenterade, kan dessa valideras mot valideringsdata och var det möjligt se om segmenterade avbördningskurvor blev överparametriserade. Studien visade att segmenterade avbördningskurvor vid kalibrering, interpolation och extrapolation generellt inte gav bättre prediktion än osegmenterade avbördningskurvor. Vid låga flöden och tydligt motiverade segmenteringar gav segmenterade avbördningskurvor en bättre interpolation, men dock inte vid extrapolation, vilket är en indikation att segmenterade avbördningskurvor var något överparametriserade. Den största inverkan på att minska felen i avbördningskurvor var var att minska mätosäkerheten i flödesmätningarna. Med en genomsnittlig mätosäkerhet i flödesmätningarna på ±5 % kunde osäkerheten kvantifieras till kring 60 % för interpolerade osegmenterade avbördningskurvor vid höga flöden och kring 95 % vid låga flöden. Variansen var dock stor. Osäkerheten från modellvalideringen av extrapolation för osegmenterade avbördningskurvor vid höga flöden kvantifierades till kring 35 % vid höga flöden och kring 250 % vid låga flöden. Resultaten visade att de relativa felen från avbördningskurvor blev större för ju lägre flödet blir.   Heteroskedastitet, som kan generera osäkerheter i avbördningskurvor, visade sig vara vanligare (59 %) i osegmenterade avbördningskurvor jämfört med segmenterade (14-15 %). Även antalet flödesmätningar hade en betydelse för felen i avbördningskurvor. / Avbördningskurva, icke-linjär regression, flöde, flödesmätning, osäkerhet, validering, hydrologi, överparametrisering, vattenstånd

The aim of this thesis is to find out the relationship between the development of the economic situation in Czech regions and potential accessibility of road networks evaluated with mathematical analysis. The intent of the model is to define a relationship between the transport accessibility and economic state in municipalities in 2001, 2011 and to predict for 2021. This evaluation has been reached with the model of potential accessibility. Several methodological problems had to be solved. Model calibration was provided with respect to the reality and changes in economic state in particular geographical regions. After the first step, which was focused on finding out the optimal model for potential accessibility of road networks, the linear regression with prediction of gross added economic value in analysed regions was used. Results showed only minor growth of gross added economic value in core geographical regions in the Czech Republic. In contrary, in peripheral regions dynamic growth of gross economic added value can be expected. This thesis follows the present interest in developing a transportation geography mathematical model, which can help us to understand the road transportation accessibility and its impact on economical development. Key words Potential accessibility, linear regression,...

The aim of this diploma thesis is based on the empirical analysis to identify the relationship between the exchange rate and the interest rates in selected countries and verify the validity of the uncovered interest rate parity. In the first part, the author deals with basic theoretical and exchange rate determinants from a fundamental analysis point of view, which attempts to explain the causality between these two variables. The actual analysis was performed at three levels on monthly time series from 2010 to 2016. Graphical analysis was selected as the first stage of the analysis, also including verification of the validity of the Fisher International Effect. Later, regression and vector autoregressive analysis followed. However, the conclusions of the individual empirical parts show that the exchange rate is determined by many factors, not only by the interest rate differential, as assumed the theory of uncovered interest rate parity. These results are also related to the low quality of the estimated models. Uncovered interest rate parity has been confirmed in very few cases, but none of the monitored currency pairs has been validated at all three levels of empirical analysis at the same time. The work offers valuable insight into the trend appreciation or depreciation of the exchange rates at the positive interest rate differential in the selected period.