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Statistická klasifikace pomocí zobecněných lineárních modelů. / Statistical Classification by means of generalized linear modelsSladká, Vladimíra January 2010 (has links)
The goal of this thesis is introduce the theory of generalized linear models, namely probit and logit model. This models are especially used for medical data processing. In our concrete case these mentioned models are applied to data file obtained in teaching hospital Brno. The aim is statically analyzed immune response of child patients in dependence of twelve selected types of genes and find out which combinations of these genes influence septic state of patients.
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Inference in Generalized Linear Models with ApplicationsByrne, Evan 29 August 2019 (has links)
No description available.
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Genetic Heterogeneity of Residual Variance for Production and Functional Traits in American Angus CattleAmorim, Sabrina Thaise 14 August 2024 (has links)
Beef cattle are continuously selected for different traits and the success in improving these traits has been remarkable. However, for certain traits, it is essential not only to improve the average performance, but also to control the variation around the mean. There is evidence that residual variance may be under genetic control, which opens the possibility of selecting for uniformity. In this sense, the objectives of the present dissertation were: 1) to investigate the extent of genetic heterogeneity of residual variance at the pedigree level in birth weight (BW), weaning weight (WW), yearling weight (YW), foot angle (FA), and claw set (CS) in American Angus cattle; 2) to compare the results of different genetic heterogeneity models; 3) to evaluate the effectiveness of Box-Cox transformation in continuous traits; and 4) to address limitations and explore alternative solutions for implementing genetic parameters for residual variance in genetic evaluations. The first study investigated the genetic heterogeneity of residual variances for BW, WW, and YW. Three models were compared: a homoscedastic residual variance model (M1), a double hierarchical generalized linear model (DHGLM, M2), and a genetically structured environmental variance model (MCMC, M3). The results showed significant genetic heterogeneity of residual variances in growth traits, suggesting the possibility of selection for uniformity. The genetic coefficient of variation for residual variance ranged from 0.90 to 0.92 in M2 and 0.31 to 0.38 in M3 for BW, 0.64 in M2 and 0.01 to 0.29 in M3 for WW, and 0.67 to 0.63 in M2 and 0.25 to 0.31 in M3 for YW. Low heritability estimates for residual variance were found, particularly in M2 (0.08 for BW, 0.06 for WW, and 0.09 for YW). The study identified both negative and positive genetic correlations between mean and residual variance, depending on the trait and data transformation. Negative correlations suggest the potential to increase trait means while decreasing residual variance. However, positive correlations indicate that the genetic response to selection for uniformity may be limited unless a selection index is used. Data transformation reduced skewness but did not eliminate genetic heterogeneity of residual variances. The Bayesian approach provided higher estimates of additive genetic variance for residual variance compared to DHGLM. Overall, the findings indicate the potential to reduce variability through selection and lay the groundwork for incorporating uniformity of growth traits into breeding goals. The second study focused on the genetic heterogeneity of residual variance for two foot conformation traits, FA and CS. Using 45,667 phenotypic records collected between 2009 and 2021, three models were compared: a traditional homoscedastic residual variance model (M1), a DHGLM (M2), and a genetically structured environmental variance model (M3). Results showed that heritability estimates for FA and CS means were within expected ranges, although lower in M2. Despite low heritability estimates for residual variance (0.07 for FA and 0.05 for CS in M2), significant genetic coefficients of variation were found, suggesting that selection on trait mean would also influence residual variance. Positive genetic correlations between mean and residual variance in M2 and M3 indicate that selection for uniformity is feasible, but may require additional strategies such as selection indices. The study highlights the potential of FA and CS as indicators for breeding programs aimed at improving production uniformity in beef cattle. Our findings suggest that selection for uniformity in growth and foot score traits in beef cattle may be limited by low heritability of residual variance and moderate to high positive genetic correlations between mean and residual variance. This was observed for most of the traits studied. To overcome these challenges, further research is needed, particularly to explore genomic information to improve the prediction accuracy of estimated breeding values (EBV) for residual variance. Although studies of uniformity using genomic data are limited, they have shown improved EBV accuracy for residual variance. Additionally, alternative methods for measuring uniformity, such as different uniformity or resilience indicators, should be considered, especially with advances in digital phenotyping. Precision livestock farming technologies that allow for extensive data collection on various production traits should be integrated into the development of new uniformity indicators. This dissertation provides valuable insights into the genetic heterogeneity of residual variance in American Angus cattle and highlights the complexity of selecting for uniformity while improving mean traits. Continued research with larger data sets, genomic information, and further methodological refinement will be critical to advance these findings to improve uniformity and productivity in beef cattle breeding. / Doctor of Philosophy / Uniformity in livestock breeding refers to the goal of reducing variability in certain traits within a livestock population to achieve more consistent and predictable outcomes. This is particularly important for traits that affect productivity, economic efficiency, animal welfare, and product quality. By achieving greater uniformity, producers can optimize management practices, improve marketability, and enhance the overall efficiency of animal production systems. Residual variance refers to the variation in traits that is not explained by known genetic or environmental factors. Recent research suggests that residual variance may be under genetic control, meaning that it is possible to select animals that not only have desirable traits, but also have less variability in those traits. Therefore, this dissertation investigates the genetic control of residual variance that may allow selection for uniformity in traits. The research focused on American Angus cattle and aimed to 1) investigate genetic heterogeneity of residual variance in traits, such as birth weight, weaning weight, yearling weight, foot angle, and claw set; 2) compare different genetic models; 3) evaluate the effectiveness of data transformations; and 4) address limitations in genetic evaluations. The first study examined genetic heterogeneity in growth traits using three models. It revealed significant genetic variability, suggesting the potential for selection for uniformity. The study found both positive and negative genetic correlations between trait means and residual variance, indicating varying potential for reducing variance while improving trait means. Data transformations reduced skewness but did not eliminate genetic heterogeneity. A Bayesian approach provided higher estimates of genetic variance than other methods. The second study focused on foot conformation traits with over 45,000 records. The study showed that despite low heritability for residual variance, there was significant genetic variation, indicating the possibility of altering residual variance through selection. Positive genetic correlations suggested that additional strategies, such as selection indices, may be needed to achieve uniformity in practice. Overall, the findings highlight the complexity of selecting for uniformity while improving average traits and underscore the need for further research, particularly using genomic data, to improve prediction accuracy. Integrating precision livestock farming technologies could help develop new indicators of uniformity, improving productivity and uniformity in beef cattle breeding.
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Tests pour la dépendance entre les sections dans un modèle de PoissonRoussel, Arnaud 05 1900 (has links)
Les simulations et figures ont été réalisées avec le logiciel R. / Pour des données de panel, les mesures répétées dans le temps peuvent remettre
en cause l’hypothèse d’indépendance entre les individus. Des tests ont été
développés pour pouvoir vérifier s’il reste de la dépendance entre les résidus d’un
modèle. Les trois tests que nous présentons dans ce mémoire sont ceux de Pesaran
(2004), Friedman (1937) et Frees (1995). Ces trois tests se basent sur les résidus
(et leurs corrélations) et ont été construits pour des modèles linéaires. Nous voulons
étudier dans ce mémoire les performances de ces trois tests dans le cadre d’un
modèle linéaire généralisé de Poisson. Dans ce but, on compare tout d’abord leurs
performances (niveaux et puissances) pour deux modèles linéaires, l’un ayant un
terme autorégressif et l’autre non. Par la suite, nous nous intéressons à leurs performances
pour un modèle linéaire généralisé de Poisson en s’inspirant de Hsiao,
Pesaran et Pick (2007) qui adaptent le test de Pesaran (2004) pour un modèle
linéaire généralisé. Toutes nos comparaisons de performances se feront à l’aide de
simulations dans lesquelles nous ferons varier un certain nombre de paramètres
(nombre d’observations, force de la dépendance, etc.). Nous verrons que lorsque
les corrélations sont toutes du même signe, le test de Pesaran donne en général
de meilleurs résultats, à la fois dans les cas linéaires et pour le modèle linéaire
généralisé. Le test de Frees présentera de bonnes propriétés dans le cas où le signe
des corrélations entre les résidus alterne. / For panel data, repeated measures over time can challenge the hypothesis of
dependence between subjects. Tests were developped in order to assess if some
dependence remains among residuals. The three tests we present in this master
thesis are from Pesaran (2004), Friedman (1937) and Frees (1995). These three
tests, constructed specifically for linear models, are based on the residuals generated
from models (and their correlations). We wish to study in this master thesis
the performances of these three tests in the case of generalized linear Poisson
models. For that goal, we compare them between each other (level, power, etc.)
using two linear models, one with an autoregressive term and the other without.
Next, inspired by Hsiao, Pesaran and Pick (2007) who adapt the test from Pesaran
(2004), we will study their performances in a generalized Poisson model.
All of our comparisons are done with simulations by modifying some variables
(number of observations, strength of the dependence). We will observe that when
the correlation is always of the same sign, Pesaran’s test is the best in most cases,
for the linear models and the generalized linear model. Frees’ test will show good
performances when the sign of the correlations alternates.
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Spotřební chování / Consumer BehaviourBabáková, Andrea January 2010 (has links)
The thesis focuses on investigating and searching for differences between consumer behavior of Czech and Slovak households depending on chosen socioeconomic factors. For the purpose of this thesis source materials are taken mainly from researches realized by Czech and Slovak Statistical Office, specifically from survey sampling Household Budget Study 2009. Data are analyzed through the use of comprehensive characteristics of location, variability and box diagrams. Generalized linear models are used for modeling dependence of consumer behavior on chosen quantitative and qualitative factors. Household consumer behavior is expressed through economic index - propensity to consume - which is determined by the share of total monthly income and expenditures.
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Relação entre poluição do ar e internações de adultos por doenças cardiovasculares totais em São Paulo entre 2000 e 2013Bezerra, Yuri Charllub Pereira 30 January 2017 (has links)
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Previous issue date: 2017-01-30 / This observational, ecological time series study aims to verify the relationship between adult hospitalizations for total cardiovascular diseases (CVDD) and air pollution stratified by sex in residents of the city of São Paulo from 2000 to 2013, observing their Structure of lag. Analyzes were stratified by age group and sex and included hospitalizations for Total Cardiovascular Diseases (ICD10: Chapter IX - I00-I99). The pollutant and meteorological data were provided by the Environmental Sanitation Technology Company of the State of São Paulo. The relationship between air pollutants and climatic factors in hospitalizations for Total Cardiovascular Diseases was analyzed by means of a polynomial distribution lag model for both temperature and air pollutants with a lag structure of up to 6 days after exhibition. Generalized linear models of Poisson regression were used, controlling for long-term seasonality, days of the week, and holidays. The following was calculated the increase in the number of hospitalizations for the interquartile difference of the pollutants significant in the regression model, as well as for the meteorological factors. For all hospital admissions for Total Cardiovascular Diseases, acute short-term effects were observed. The O3 was the only pollutant that did not have any relation to any of the analyzed results and NO2 had the greater effect, for an increase of interquartile 50.22 ¿g / m 3 of NO2, an increase of 13.09% (IC95 %: 4.74% - 21.45%), among the total admissions from 30 to 44 years. Stratifying the analysis by age group, a greater effect was found for hospitalizations from 45 to 60 years. Regarding gender, between the age group 30 and 44, the men stood out, and for the 45-60 age group, the women were more affected than the men. / Este estudo observacional, ecológico de series temporais tem por objetivo de verificar a relação entre internações de adultos por doenças cardiovasculares totais (DCVT) e poluição do ar estratificado por sexo, em residentes do município de São Paulo no período de 2000 a 2013, observando sua estrutura de defasagem. As analises foram estratificadas por faixa etária e sexo e incluíram internações por Doenças Cardiovasculares Totais (CID10: capítulo IX - I00-I99). Os dados de poluentes e meteorológicos foram fornecidos pela Companhia de Tecnologia de Saneamento Ambiental do Estado de São Paulo. A relação entre poluentes do ar e fatores climáticos nas internações por Doenças Cardiovasculares Totais, foram analisadas por meio de um modelo de defasagem de distribuição polinomial tanto para a temperatura como para os poluentes do ar, com uma estrutura de defasagem de até 6 dias após a exposição. Foram utilizados modelos lineares generalizados de regressão de Poisson, controlando-se para sazonalidade de longa duração, dias da semana e feriados. A seguir foi calculado o aumento no número de internações para a diferença interquartil dos poluentes significativos no modelo de regressão, bem como para os fatores meteorológicos. Para todas as admissões hospitalares por Doenças Cardiovasculares Totais, foram observados efeitos agudos de curta duração. O O3 foi o único poluente que não teve relação a nenhum dos desfechos analisados e o NO2 foi o que teve o efeito maior, para um aumento de interquartil 50,22 µg/m³ de NO2, revelou um aumento de 13,09% (IC95%: 4,74% - 21,45%), entre as internações totais de 30 a 44 anos. Estratificando a análise por faixa etária, encontrou-se um maior efeito para as internações de 45 a 60 anos. No que diz respeito ao sexo, entre a faixa etária 30 a 44, sobressaíram os homens, e para a faixa etária de 45 a 60 anos, as mulheres foram mais afetadas que os homens.
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Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic EvaluationShen, Xia January 2012 (has links)
This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision. Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes. The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).
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Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic EvaluationShen, Xia January 2012 (has links)
This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision. Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes. The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).
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Crescimento de espécies florestais madeiráveis como subsídio para o manejo florestal na Amazônia ocidental / Growth of forest timber species as improvements to the forest management in western AmazonCunha, Thiago Augusto da 25 February 2013 (has links)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Reliable growth data from trees are very important in the context of forest
management. Tree-characteristics such as architecture and competition are
associated with diameter growth. Previous studies analyzing tree growth changes
have indicated that these variables can describe these effects more effectively.
However, the precise role of these effects in the growth modeling of tropical trees
needs to be studied further to discuss more effectively the actual forest management
practices. Here, we reconstructed the periodic annual basal area increment (IPAg) of
four long-lived timber species from the Amazon forest: Cedro (Cedrela odorata);
Cerejeira (Amburana cearensis); Copaíba (Copaifera paupera) e Mogno (Swietenia
macrophylla) aiming to explain the IPAg variation by developing a individua-tree
growth model using the following potential predictors: tree size, morphometric data,
competition; crown position and liana load. The model was fitted using a Gamma
distribution in the context of Generalized Linear Models. The statistics criteria and
residual distributions showed that growth model was adequate to adjust the observed
IPAg data and revealed some dendrometric variables that were involved into the
effects that lead the observed variation in IPAg, presenting a broad range of the
observed data in situations were growth is complex and variable between species.
Trees sampled in good site conditions - expressed as a good crown exposure to light,
and therefore low competition - presented higher growth rates than trees sampled
under high competition from neighboring trees. Besides, the variables Liana load, for
Cedrela, the crown diameter and the Hegyi competition index was demonstrated to
be highly influential predictive variable. Also, trees sampled in densities greater than
25 m2.ha-1 had their IPAg% significantly reduced. In the context of basal area
increment yield by the space occupied in the forest (crown efficiency) the species
presented mostly efficiency when growth in dominant position with thin and long
crown (crown formal). Among the species, Cedrela odorata was the most efficient in
growth. This behavior reinforces the importance of release trees to obtain better
crown exposure. / Dados confiáveis de crescimento de árvores são muito importantes no contexto do
manejo florestal. Características próprias da árvore como a arquitetura e a
competição estão associadas diretamente com o crescimento em diâmetro e altura.
Estudos anteriores indicaram que essas variáveis podem descrever a variação do
incremento. No entanto, o efeito dessas variáveis na modelagem do crescimento de
árvores tropicais precisa ser mais bem estudado, para discutir efetivamente as
praticas de manejo florestal atuais. Portanto, nessa pesquisa reconstruiu-se o
incremento periódico anual em área basal (IPAg) de quatro espécies de árvores
madeiráveis de vida longa da Amazônia: Cedro (Cedrela odorata); Cerejeira
(Amburana cearensis); Copaíba (Copaifera paupera) e Mogno (Swietenia
macrophylla) com o objetivo de explicar a variação de IPAg, propondo um modelo de
crescimento tipo de árvore individual utilizando os seguintes preditores potenciais:
tamanho e morfometria da árvore; o status competitivo; a posição social e a carga de
lianas na copa. O modelo foi ajustado considerando a distribuição de probabilidade
Gama no contexto de Modelo Linear Generalizado. Em base a critérios estatísticos e
avaliação residual, o modelo de crescimento demonstrou ser adequado para explicar
a variação de IPAg e revelou variáveis dendrométricas que englobam grande parte
dos efeitos que moldaram a variação observada do IPAg, apresentando boa
abrangência dos dados observados em situações onde o crescimento é complexo e
variado entre as espécies. As árvores quando amostradas em boas condições de
sítio, expressado por boa exposição da copa à luz solar e, portanto, pouca
competição, apresentaram as maiores taxas de IPAg, no período avaliado, do que
aquelas encontradas sob forte competição por árvores vizinhas. Além disso, as
variáveis carga de lianas na copa, para Cedrela, o diâmetro de copa e o status
competitivo de Hegyi influenciaram de forma significativa o IPAg. Árvores
amostradas em densidade maior do que 25 m2.ha-1 mostraram queda significativa do
IPAg%. No contexto de incremento em área basal por área ocupada na floresta
(eficiência da copa), todas as quatro espécies mostraram-se mais eficientes quando
em melhor posição social e quando com copas estreitas e longas (formal de copa
pequeno). Entre as espécies a Cedrela odorata foi a mais eficiente no crescimento,
comportamento que reforça a importância da liberação das árvores o que
proporcionaria melhor exposição da copa à luz solar.
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Aspekty kolaborativních nákupů: Centralizace, rozsah a rozdílné tržní struktury / The Aspects of Collaborative Procurement: Centralization, Scope and Different Market StructuresPočarovská, Amália January 2018 (has links)
Procurement centralization is a process that includes policy decisions on the appropriate level of collaboration, aggregation and standardization. We analyse the main aspects of collaborative procurement: centralization, scope and different market structures. We use a unique dataset that combines Czech tender-level data with the manually-collected data on centrally procured tenders and financial firm-level data for the time span 2008 - 2016. We apply vector generalized linear model to the compulsory centralized procurement sectors and assess the market competition and concentration. We find several key aspects of centralized procurement: the centralization has a significant positive impact on the competition in selected sectors. The framework agreement is recognized as a positive setup of public procurement. We identified a strong negative evidence of the heterogeneity of the procured commodity. The design of centralization process and the degree of centralization is always bound by two elementary questions: the flexibility or unification trade-off and the set-up costs or unit costs trade-off. JEL Classification D44, H11, H57 Keywords public procurement, centralization, tender- level data, firm-level data, market structure, concentration index, vector generalized linear model, Herfindahl-Hirschman...
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