995 resultados para Binomial Distribution
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Injection of min K mRNA into Xenopus oocytes results in expression of slowly activating voltage-dependent potassium channels, distinct from those induced by expression of other cloned potassium channels. The min K protein also differs in structure, containing only a single predicted transmembrane domain. While it has been demonstrated that all other cloned potassium channels form by association of four independent subunits, the number of min K monomers which constitute a functional channel is unknown. In rat min K, replacement of Ser-69 by Ala (S69A) causes a shift in the current-voltage (I-V) relationship to more depolarized potentials; currents are not observed at potentials negative to 0 mV. To determine the subunit stoichiometry of min K channels, wild-type and S69A subunits were coexpressed. Injections of a constant amount of wild-type mRNA with increasing amounts of S69A mRNA led to potassium currents of decreasing amplitude upon voltage commands to -20 mV. Applying a binomial distribution to the reduction of current amplitudes as a function of the different coinjection mixtures yielded a subunit stoichiometry of at least 14 monomers for each functional min K channel. A model is presented for how min K subunits may form a channel.
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Cystic echinococcosis, caused by Echinococcus grantilosus, is highly endemic in North Africa and the Middle East. This paper examines the abundance and prevalence of infection of E. granulosus in camels in Tunisia. No cysts were found in 103 camels from Kebili, whilst 19 of 188 camels from Benguerden (10.1%) were infected. Of the cysts found 95% were considered fertile with the presence of protoscolices and 80% of protoscolices were considered viable by their ability to exclude aqueous eosin. Molecular techniques were used on cyst material from camels and this demonstrated that the study animals were infected with the G1 sheep strain of E. granulosus. Observed data were fitted to a mathematical model by maximum likelihood techniques to define the parameters and their confidence limits and the negative binomial distribution was used to define the error variance in the observed data. The infection pressure to camels was somewhat lower in comparison to sheep reported in an earlier study. However, because camels are much longer-lived animals, the results of the model fit suggested that older camels have a relatively high prevalence rate, reaching a most likely value of 32% at age 15 years. This could represent an important source of transmission to dogs and hence indirectly to man of this zonotic strain. In common with similar studies on other species, there was no evidence of parasite-induced immunity in camels. (C) 2004 Elsevier B.V. All rights reserved.
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Stochastic models based on Markov birth processes are constructed to describe the process of invasion of a fly larva by entomopathogenic nematodes. Various forms for the birth (invasion) rates are proposed. These models are then fitted to data sets describing the observed numbers of nematodes that have invaded a fly larval after a fixed period of time. Non-linear birthrates are required to achieve good fits to these data, with their precise form leading to different patterns of invasion being identified for three populations of nematodes considered. One of these (Nemasys) showed the greatest propensity for invasion. This form of modelling may be useful more generally for analysing data that show variation which is different from that expected from a binomial distribution.
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O presente estudo cefalométrico retrospectivo teve como objetivo avaliar a influência do padrão esquelético sagital na determinação do padrão esquelético vertical da face (Tipo Facial) em indivíduos com diferentes más oclusões, que procuraram a UMESP para tratamento ortodôntico nos últimos 10 anos. Para isso foram selecionadas as telerradiografias iniciais de 59 pacientes, com idade média de 16 anos e 7 meses variando entre 11 e 25 anos. Estes pacientes foram selecionados após a análise facial subjetiva de 1600 documentações, resultando em 3 grupos. Grupo 1 Padrão I facial; Grupo 2 - Padrão II; e, Grupo 3 - Padrão III. Após esta divisão, foi comparado se a determinação do tipo facial é diferente nas medidas angulares SN.GoGn e SN.Gn. Para testar essa hipótese, utilizou-se uma regressão logística com erros distribuídos de acordo com uma distribuição binomial. Para observar a probabilidade de uma congruência entre SN.Gn e SN.GoGn utilizou-se uma regressão logística individual para cada Padrão Facial. Observou-se que a probabilidade de uma congruência entre SN.Gn e SN.GoGn no Padrão I é relativamente alta (70%), mas para os Padrões II e III essa congruência é relativamente baixa - Padrão II (46%) e Padrão III (37%). O Padrão esquelético sagital da face (Padrão I, II e III) influencia na determinação do Tipo Facial. Utilizar a grandeza SN.Gn parece não ser apropriado para a determinação do Padrão esquelético vertical da face, em virtude do ponto Gn sofrer importantes deslocamentos nos diferentes Padrões Faciais.
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This work was supported by the Bulgarian National Science Fund under grant BY-TH-105/2005.
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Crash reduction factors (CRFs) are used to estimate the potential number of traffic crashes expected to be prevented from investment in safety improvement projects. The method used to develop CRFs in Florida has been based on the commonly used before-and-after approach. This approach suffers from a widely recognized problem known as regression-to-the-mean (RTM). The Empirical Bayes (EB) method has been introduced as a means to addressing the RTM problem. This method requires the information from both the treatment and reference sites in order to predict the expected number of crashes had the safety improvement projects at the treatment sites not been implemented. The information from the reference sites is estimated from a safety performance function (SPF), which is a mathematical relationship that links crashes to traffic exposure. The objective of this dissertation was to develop the SPFs for different functional classes of the Florida State Highway System. Crash data from years 2001 through 2003 along with traffic and geometric data were used in the SPF model development. SPFs for both rural and urban roadway categories were developed. The modeling data used were based on one-mile segments that contain homogeneous traffic and geometric conditions within each segment. Segments involving intersections were excluded. The scatter plots of data show that the relationships between crashes and traffic exposure are nonlinear, that crashes increase with traffic exposure in an increasing rate. Four regression models, namely, Poisson (PRM), Negative Binomial (NBRM), zero-inflated Poisson (ZIP), and zero-inflated Negative Binomial (ZINB), were fitted to the one-mile segment records for individual roadway categories. The best model was selected for each category based on a combination of the Likelihood Ratio test, the Vuong statistical test, and the Akaike's Information Criterion (AIC). The NBRM model was found to be appropriate for only one category and the ZINB model was found to be more appropriate for six other categories. The overall results show that the Negative Binomial distribution model generally provides a better fit for the data than the Poisson distribution model. In addition, the ZINB model was found to give the best fit when the count data exhibit excess zeros and over-dispersion for most of the roadway categories. While model validation shows that most data points fall within the 95% prediction intervals of the models developed, the Pearson goodness-of-fit measure does not show statistical significance. This is expected as traffic volume is only one of the many factors contributing to the overall crash experience, and that the SPFs are to be applied in conjunction with Accident Modification Factors (AMFs) to further account for the safety impacts of major geometric features before arriving at the final crash prediction. However, with improved traffic and crash data quality, the crash prediction power of SPF models may be further improved.
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A class of multi-process models is developed for collections of time indexed count data. Autocorrelation in counts is achieved with dynamic models for the natural parameter of the binomial distribution. In addition to modeling binomial time series, the framework includes dynamic models for multinomial and Poisson time series. Markov chain Monte Carlo (MCMC) and Po ́lya-Gamma data augmentation (Polson et al., 2013) are critical for fitting multi-process models of counts. To facilitate computation when the counts are high, a Gaussian approximation to the P ́olya- Gamma random variable is developed.
Three applied analyses are presented to explore the utility and versatility of the framework. The first analysis develops a model for complex dynamic behavior of themes in collections of text documents. Documents are modeled as a “bag of words”, and the multinomial distribution is used to characterize uncertainty in the vocabulary terms appearing in each document. State-space models for the natural parameters of the multinomial distribution induce autocorrelation in themes and their proportional representation in the corpus over time.
The second analysis develops a dynamic mixed membership model for Poisson counts. The model is applied to a collection of time series which record neuron level firing patterns in rhesus monkeys. The monkey is exposed to two sounds simultaneously, and Gaussian processes are used to smoothly model the time-varying rate at which the neuron’s firing pattern fluctuates between features associated with each sound in isolation.
The third analysis presents a switching dynamic generalized linear model for the time-varying home run totals of professional baseball players. The model endows each player with an age specific latent natural ability class and a performance enhancing drug (PED) use indicator. As players age, they randomly transition through a sequence of ability classes in a manner consistent with traditional aging patterns. When the performance of the player significantly deviates from the expected aging pattern, he is identified as a player whose performance is consistent with PED use.
All three models provide a mechanism for sharing information across related series locally in time. The models are fit with variations on the P ́olya-Gamma Gibbs sampler, MCMC convergence diagnostics are developed, and reproducible inference is emphasized throughout the dissertation.
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Este estudio presenta la validación de las observaciones que realizó el programa de observación pesquera llamado Programa Bitácoras de Pesca (PBP) durante el periodo 2005 - 2011 en el área de distribución donde operan las embarcaciones industriales de cerco dedicadas a la pesca del stock norte-centro de la anchoveta peruana (Engraulis ringens). Además, durante ese mismo periodo y área de distribución, se estimó la magnitud del descarte por exceso de captura, descarte de juveniles y la captura incidental de dicha pesquera. Se observaron 3 768 viajes de un total de 302 859, representando un porcentaje de 1.2 %. Los datos del descarte por exceso de captura, descarte de juveniles y captura incidental registrados en los viajes observados, se caracterizaron por presentar un alta proporción de ceros. Para la validación de las observaciones, se realizó un estudio de simulación basado en la metodología de Monte Carlo usando un modelo de distribución binomial negativo. Esta permite inferir sobre el nivel de cobertura óptima y conocer si la información obtenida en el programa de observación es contable. De este análisis, se concluye que los niveles de observación actual se deberían incrementar hasta tener un nivel de cobertura de al menos el 10% del total de viajes que realicen en el año las embarcaciones industriales de cerco dedicadas a la pesca del stock norte-centro de la anchoveta peruana. La estimación del descarte por exceso de captura, descarte de juveniles y captura incidental se realizó mediante tres metodologías: Bootstrap, Modelo General Lineal (GLM) y Modelo Delta. Cada metodología estimó distintas magnitudes con tendencias similares. Las magnitudes estimadas fueron comparadas usando un ANOVA Bayesiano, la cual muestra que hubo escasa evidencia que las magnitudes estimadas del descarte por exceso de captura por metodología sean diferentes, lo mismo se presentó para el caso de la captura incidental, mientras que para el descarte de juveniles mostró que hubieron diferencias sustanciales de ser diferentes. La metodología que cumplió los supuestos y explico la mayor variabilidad de las variables modeladas fue el Modelo Delta, el cual parece ser una mejor alternativa para la estimación, debido a la alta proporción de ceros en los datos. Las estimaciones promedio del descarte por exceso de captura, descarte de juveniles y captura incidental aplicando el Modelo Delta, fueron 252 580, 41 772, 44 823 toneladas respectivamente, que en conjunto representaron el 5.74% de los desembarques. Además, con la magnitud de la estimación del descarte de juveniles, se realizó un ejercicio de proyección de biomasa bajo el escenario hipotético de no mortalidad por pesca y que los individuos juveniles descartados sólo presentaron tallas de 8 y 11 cm., en la cual se obtuvo que la biomasa que no estará disponible a la pesca está entre los 52 mil y 93 mil toneladas.
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Human radiosensitivity is a quantitative trait that is generally subject to binomial distribution. Individual radiosensitivity, however, may deviate significantly from the mean (by 2-3 standard deviations). Thus, the same dose of radiation may result in different levels of genotoxic damage (commonly measured as chromosome aberration rates) in different individuals. There is significant genetic component in individual radiosensitivity. It is related to carriership of variant alleles of various single-nucleotide polymorphisms (most of these in genes coding for proteins functioning in DNA damage identification and repair); carriership of different number of alleles producing cumulative effects; amplification of gene copies coding for proteins responsible for radioresistance, mobile genetic elements, and others. Among the other factors influencing individual radioresistance are: radioadaptive response; bystander effect; levels of endogenous substances with radioprotective and antimutagenic properties and environmental factors such as lifestyle and diet, physical activity, psychoemotional state, hormonal state, certain drugs, infections and others. These factors may have radioprotective or sensibilising effects. Apparently, there are too many factors that may significantly modulate the biological effects of ionising radiation. Thus, conventional methodologies for biodosimetry (specifically, cytogenetic methods) may produce significant errors if personal traits that may affect radioresistance are not accounted for.
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2016
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A probabilistic model for intra-familial distribution of infectous disease is proposed and applied to the prevalence of positive serology for Trypanosoma cruzi infection in Northeastern Brazilian sample. This double with one tail excess model fits satisfactorily to the data and its interpretation says that around 51% of these 982 families are free of infection risk; among those that are at risk, 3% have a high risk (0.66), probably due to high domestic infestation of the vector bug; while 97% show a small risk (0.11), probably due to accidental, non-domestic transmission.
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Aim To assess the geographical transferability of niche-based species distribution models fitted with two modelling techniques. Location Two distinct geographical study areas in Switzerland and Austria, in the subalpine and alpine belts. Methods Generalized linear and generalized additive models (GLM and GAM) with a binomial probability distribution and a logit link were fitted for 54 plant species, based on topoclimatic predictor variables. These models were then evaluated quantitatively and used for spatially explicit predictions within (internal evaluation and prediction) and between (external evaluation and prediction) the two regions. Comparisons of evaluations and spatial predictions between regions and models were conducted in order to test if species and methods meet the criteria of full transferability. By full transferability, we mean that: (1) the internal evaluation of models fitted in region A and B must be similar; (2) a model fitted in region A must at least retain a comparable external evaluation when projected into region B, and vice-versa; and (3) internal and external spatial predictions have to match within both regions. Results The measures of model fit are, on average, 24% higher for GAMs than for GLMs in both regions. However, the differences between internal and external evaluations (AUC coefficient) are also higher for GAMs than for GLMs (a difference of 30% for models fitted in Switzerland and 54% for models fitted in Austria). Transferability, as measured with the AUC evaluation, fails for 68% of the species in Switzerland and 55% in Austria for GLMs (respectively for 67% and 53% of the species for GAMs). For both GAMs and GLMs, the agreement between internal and external predictions is rather weak on average (Kulczynski's coefficient in the range 0.3-0.4), but varies widely among individual species. The dominant pattern is an asymmetrical transferability between the two study regions (a mean decrease of 20% for the AUC coefficient when the models are transferred from Switzerland and 13% when they are transferred from Austria). Main conclusions The large inter-specific variability observed among the 54 study species underlines the need to consider more than a few species to test properly the transferability of species distribution models. The pronounced asymmetry in transferability between the two study regions may be due to peculiarities of these regions, such as differences in the ranges of environmental predictors or the varied impact of land-use history, or to species-specific reasons like differential phenotypic plasticity, existence of ecotypes or varied dependence on biotic interactions that are not properly incorporated into niche-based models. The lower variation between internal and external evaluation of GLMs compared to GAMs further suggests that overfitting may reduce transferability. Overall, a limited geographical transferability calls for caution when projecting niche-based models for assessing the fate of species in future environments.
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We analyze data obtained from a study designed to evaluate training effects on the performance of certain motor activities of Parkinson`s disease patients. Maximum likelihood methods were used to fit beta-binomial/Poisson regression models tailored to evaluate the effects of training on the numbers of attempted and successful specified manual movements in 1 min periods, controlling for disease stage and use of the preferred hand. We extend models previously considered by other authors in univariate settings to account for the repeated measures nature of the data. The results suggest that the expected number of attempts and successes increase with training, except for patients with advanced stages of the disease using the non-preferred hand. Copyright (c) 2008 John Wiley & Sons, Ltd.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Includes bibliography