Dry months in the agricultural region of Ribeirão Preto, state of São Paulo-Brazil: an study based on the extreme value theory

Blain, Gabriel Constantino

doi:10.1590/s0100-69162014000500018

Cited by 5 publications

(4 citation statements)

References 23 publications

(45 reference statements)

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“…With the parameters estimated, goodness of fit criteria of the GPD model were evaluated. The Kolmogorov Smirnov (KS) test was used to compare the theoretical cumulative distribution and the empirical cumulative distribution [28]. The Ljung Box (LB) independence test, whose statistics are compared with the -th quantile of the chi-squared distribution with one degree of freedom.…”

Section: Hypothesis Testingmentioning

confidence: 99%

Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil

et al. 2020

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The rainfall monitoring allows us to understand the hydrological cycle that not only influences the ecological and environmental dynamics, but also affects the economic and social activities. These sectors are greatly affected when rainfall occurs in amounts greater than the average, called extreme event; moreover, statistical methodologies based on the mean occurrence of these events are inadequate to analyze these extreme events. The Extreme Values Theory provides adequate theoretical models for this type of event; therefore, the Generalized Pareto Distribution (Henceforth GPD) is used to analyze the extreme events that exceed a threshold. The present work has applied both the GPD and its nested version, the Exponential Distribution, in monthly rainfall data from the city of Uruguaiana, in the state of Rio Grande do Sul in Brazil, which calculates the return levels and probabilities for some events of practical interest. To support the results, the goodness of fit criteria is used, and a Monte Carlo simulation procedure is proposed to detect the true probability distribution in each month analyzed. The results show that the GPD and Exponential Distribution fits to the data in all months. Through the simulation study, we perceive that the GPD is more suitable in the months of September and November. However, in January, March, April, and August the, Exponential Distribution is more appropriate, and in the other months, we can use either one.

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Section: Hypothesis Testingmentioning

confidence: 99%

Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil

et al. 2020

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“…A verificação do ajuste da distribuição Gumbel aos dados pode ser feita mediante um teste de aderência. Para tal, foi utilizado o teste de Kolmogorov-Smirnov, em conformidade com Blain (2014), adotando 5% como nível de signi-ficância. A verificação da precisão das estimativas dos parâmetros da distribuição Gumbel foi feita utilizando o Erro Padrão Relativo das estimativas dos parâmetros μ e σ , que são dados por: Dada a especificação da distribuição Gumbel e suas estimativas de parâmetros, é possível proceder com o cálculo de probabilidades.…”

Section: Metodologiaunclassified

Centro de Ciências Agrárias da UFSCar

2023

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Carlos (UFSCar) têm uma história muito mais antiga dos que os 30 anos comemorados em 2021. Dos cafezais do século XIX sobraram as construções, em especial a senzala, que nos faz pensar sobre um período que deixou marcas profundas em nossa sociedade e que estão presentes até hoje. A cana-de-açúcar substituiu gradativamente o café e nos anos 1950 foi implementado o Instituto do Açúcar e do Álcool (IAA), instituição federal que foi protagonista no melhoramento da cana-de-açúcar, atividade até hoje extremamente relevante no CCA. No início dos anos 1990, mudanças nas políticas públicas federais decretaram a extinção do IAA, que foi incorporado à UFSCar. Surgiram o campus Araras e o CCA. E nada mais natural que suas atividades fossem iniciadas com o curso de graduação em Engenharia Agronômica. Sua expansão acadêmica começou nos anos 2000 e se consolidou nos anos 2010 com os cursos do Programa de Apoio a Planos de Reestruturação e Expansão das Universidades Federais (Reuni). Hoje somos cinco departamentos acadêmicos, seis cursos de graduação e quatro de pós-graduação; pesquisas em diferentes áreas do conhecimento e com forte vocação em extensão. Somos plurais. Para celebrar os nossos 30 anos, convidamos vocês à leitura das próximas páginas, que contam um pouco sobre a nossa rica memória histórica, marcada pela recente pandemia de Covid-19 e pelo distanciamento social. Que a história nos fortaleça ainda mais!

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“…The goodness of fit for each distribution was validated using the Kolmogorov Smirnov (KS) adherence test in conjunction with the Q-Q plots [20,21]. The Q-Q plot consists of the points where F À1 p i ÀÁ is the inverse function of the cumulative distribution function of a given probability distribution, p i are the percentiles and x i are the data used to fit the model, ordered in ascending and n the sample size.…”

Section: Modeling Maximum Sensory Scores and Numerical Proceduresmentioning

confidence: 99%

Intensive Computational Method Applied for Assessing Specialty Coffees by Trained and Untrained Consumers

Liska¹,

Beijo²,

Cirillo³

et al. 2021

Recent Advances in Numerical Simulations

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The sensory analysis of coffees assumes that a sensory panel is formed by tasters trained according to the recommendations of the American Specialty Coffee Association. However, the choice that routinely determines the preference of a coffee is made through experimentation with consumers, in which, for the most part, they have no specific ability in relation to sensory characteristics. Considering that untrained consumers or those with basic knowledge regarding the quality of specialty coffees have little ability to discriminate between different sensory attributes, it is reasonable to admit the highest score given by a taster. Given this fact, probabilistic studies considering appropriate probability distributions are necessary. To access the uncertainty inherent in the notes given by the tasters, resampling methods such as Monte Carlo’s can be considered and when there is no knowledge about the distribution of a given statistic, p-Bootstrap confidence intervals become a viable alternative. This text will bring considerations about the use of the non-parametric resampling method by Bootstrap with application in sensory analysis, using probability distributions related to the maximum scores of tasters and accessing the most frequent region (mode) through computational resampling methods.

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Dry months in the agricultural region of Ribeirão Preto, state of São Paulo-Brazil: an study based on the extreme value theory

Cited by 5 publications

References 23 publications

Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil

Generalized Pareto distribution applied to the analysis of maximum rainfall events in Uruguaiana, RS, Brazil

Centro de Ciências Agrárias da UFSCar

Intensive Computational Method Applied for Assessing Specialty Coffees by Trained and Untrained Consumers

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