968 resultados para Weibull Probability Plot


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In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

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Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.

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Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

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The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

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In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

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Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

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Some Eucalyptus species are widely used as a plantation crop in tropical and subtropical regions. One reason for this is the diversity of end uses, but the main reason is the high level of wood production obtained from commercial plantings. With the advancement of biotechnology it will be possible to expand the geographical area in which eucalypts can be used as commercial plantation crops, especially in regions with current climatic restrictions. Despite the popularity of eucalypts and their increasing range, questions still exist, in both traditional planting areas and in the new regions: Can eucalypts invade areas of native vegetation, causing damage to natural ecosystems biodiversity? The objective of this study it was to assess whether eucalypts can invade native vegetation fragments in proximity to commercial stands, and what factors promote this invasive growth. Thus, three experiments were established in forest fragments located in three different regions of Brazil. Each experiment was composed of 40 plots (1 m(2) each one), 20 plots located at the border between the forest fragment and eucalypts plantation, and 20 plots in the interior of the forest fragments. In each experimental site, the plots were paired by two soil exposure conditions, 10 plots in natural conditions and 10 plots with soil exposure (no plant and no litter). During the rainy season, 2 g of eucalypts seeds were sown in each plot, including Eucalyptus grandis or a hybrid of E. urophylla x E. grandis, the most common commercial eucalypt species planted in the three region. At 15, 30, 45, 90, 180, 270 and 360 days after sowing, we assessed the number of seedlings of eucalypts and the number of seedlings of native species resulting from natural regeneration. Fifteen days after sowing, the greatest number of eucalypts seedlings (37 m(-2)) was observed in the plots with lower luminosity and exposed soil. Also, for native species, it was observed that exposed soil improved natural germination reaching the highest number of 163 seedlings per square meter. Site and soil exposure were the factors that have the greatest influence on seed germination of both eucalypt and native species. However, 270 days after sowing, eucalypt seedlings were not observed at any of the three experimental sites. The result shows the inability of eucalypts to adapt to condition outside of their natural range. However, native species demonstrated their strong capacity for natural regeneration in forest fragments under the same conditions where eucalypts were seeded. (C) 2011 Elsevier B.V. All rights reserved.

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We examined resource limitations on growth and carbon allocation in a fast-growing, clonal plantation of Eucalyptus grandis x urophylla in Brazil by characterizing responses to annual rainfall, and response to irrigation and fertililization for 2 years. Productivity measures included gross primary production (GPP), total belowground carbon allocation (TBCA), bole growth, and net ecosystem production (NEP). Replicate plots within a single plantation were established at the midpoint of the rotation (end of year 3), with treatments of no additional fertilization or irrigation, heavy fertilization (to remove any nutrient limitation), irrigation (to remove any water limitation), and irrigation plus fertilization. Rainfall was unusually high in the first year (1769mm) of the experiment, and control plots had high rates of GPP (6.64 kg C m(-2) year(-1)), TBCA (2.14 kg C m(-2) year(-1)), and bole growth (1.81 kg C m(-2) year). Irrigation increased each of these rates by 15-17%. The second year of the experiment had average rainfall (1210 mm), and lower rainfall decreased production in control plots by 46% (GPP), 52% (TBCA), and 40% (bole growth). Fertilization treatments had neglible effects. The response to irrigation was much greater in the drier year, with irrigated plots exceeding the production in control plots by 83% (GPP), 239% (TBCA), and 24% (bole growth). Even though the rate of irrigation ensured no water limitation to tree growth, the high rainfall year showed higher production in irrigated plots for both GPP (38% greater than in drier year) and bole growth (23% greater). Varying humidity and supplies of water led to a range in NEP of 0.8-2.7 kg C m(-2) year. This difference between control and irrigated treatments, combined with differences between drier and wetter years, indicated a strong response of these Eucalyptus trees to both water supply and atmospheric humidity during the dry season. The efficiency of converting light energy into fixed carbon ranged from a low of 0.027 mol C to a high of 0.060 mol C per mol of absorbed photosynthetically active radiation (APAR), and the efficiency of bolewood production ranged from 0.78 to 1.98 g wood per MJ of APAR. Irrigation increased the efficiency of wood production per unit of water used from 2.55 kg wood m(-3) in the rainfed plot to 3.51 kg m(-3) in irrigated plots. Detailed information on the response of C budgets to environmental conditions and resource supplies will be necessary for accurate predictions of plantation yields across years and landscapes. (V) 2007 Elsevier B.V. All rights reserved.

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Unsaturated hydraulic conductivity of an Oxisol, using a neutron probe. The objective of this study was to determine the unsaturated hydraulic conductivity, using a neutron probe, of a clay sandy Oxisol. The Study was carried out in the city of Piracicaba, kite of Sao Paulo, Brazil (22 degrees 42` 43.3 `` S, 47 degrees`37` 10.4 `` W, 546 m). The dimensions of the experimental plot were 45 In x 15 m, in which 40 aluminum tubes were installed in order to access a neutron probe to measure the soil water content at the depths of 0.2, 0.4, 0.6, 0.8 and 1.0 m and, then, calculate the soil water storage of the 0 - 1.0 m soil layer. The distribution of these tubes was made in grids of four columns by ten rows in spacing of 5 x 5 m. The K(theta) functions were determined in the 40 points from regression analyses of theta as function Int and h(z) as a function of Int, being K the hydraulic conductivity, theta the volumetric soil water content, h(z) the soil water storage in the 0 - Z m layer, and t the soil water redistribution time. The neutron probe proved to be an efficient equipment in determining soil water contents, in the instantaneous profile method for determination of the K(theta) function in homogeneous soil.

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Time-domain reflectometry (TDR) is an important technique to obtain series of soil water content measurements in the field. Diode-segmented probes represent an improvement in TDR applicability, allowing measurements of the soil water content profile with a single probe. In this paper we explore an extensive soil water content dataset obtained by tensiometry and TDR from internal drainage experiments in two consecutive years in a tropical soil in Brazil. Comparisons between the variation patterns of the water content estimated by both methods exhibited evidences of deterioration of the TDR system during this two year period at field conditions. The results showed consistency in the variation pattern for the tensiometry data, whereas TDR estimates were inconsistent, with sensitivity decreasing over time. This suggests that difficulties may arise for the long-term use of this TDR system under tropical field conditions. (c) 2008 Elsevier B.V. All rights reserved.

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The objective of this work was to evaluate the economic feasibility of cowpea irrigation in Piaui State Brazil. Water balances were carried out on a daily basis using the Thornthwaite and Mather (1955) method, for 165 sites, considering twelve sowings dates and available water capacity in the soil of 20, 40 and 60 mm. The net revenues were estimated with a probability of occurrence of 75%, later being spatialized to Piaui State. Cowpea irrigation was shown to economically viable for all sowing dates, irrespective of the available water capacity. Net revenues varied among several regions of the State, in function of the sowing date and available water capacity in the soil. Considering a planning strategy for Piaui State, sowing on February, I was shown to be most favorable, because it enabled higher net revenue values, covering larger areas of the State.

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The aim was to verify if the fungigation via drip irrigation is an alternative to the conventional method of spraying on tomato for controlling early blight. Tomato plants (variety Santa Clara) were grown in pots inside a greenhouse. Fifty days after transplanting, the plants were inoculated with Alternaria solani and treated with four different fungicides: azoxystrobin (8 g 100 L(-1)), difeconazole (50 mL 100 L(-1)), metiram+piraclostrobin (200 g 100 L(-1)) and tebuconazole (100 mL 100 L(-1)) using two applications methods: conventional spraying and fiingigation dripping. The control plants did not receive fungicide application. To assess the severity of the disease, we used a rating scale expressed as the area under the disease progress curve (AUDPC) and production factors, such as number, weight and average diameter of the fruit and its productivity. The experimental design was completely randomized in factorial scheme 4 x 2 + 1 with eight replicates. Each plot had one plant in one pot. A 27% reduction in disease severity was observed when compared with the control plants, with no significant difference noted regarding the application method. The number of fruits did not statistically differ between the treatments. The average weight and diameter of the fruits were superior in the plants that had fungicide application compared to the control plant, reflecting an increase in productivity. Fungigation through water dripping is an alternative to the conventional method of spraying cultured tomatoes.

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Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.

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Host suitability of oats for Pratylenchus brachyurus Black oat (Avena strigosa), white oat (A. sativa) and Algerian oat (A. byzantina) are extensively cultivated in the south of Brazil for grain, forage, hay and silage production, or as cover crop in no-tillage and crop-pasture integration systems. In both systems, the genotypes of oat used as cover crop must be nonhosts or poor hosts of damaging nematodes for summer cash crops. Taking into account the relevance of Pratylenchus brachyurus as a pathogen for many cash crops in Brazil, two experiments were carried out in a glasshouse in order to evaluate the host suitability of selected oat cultivars to this nematode. The initial population inoculated (Pi) were 92 specimens/plot in experiment 1, and 270 in experiment 2. At the end of experimental periods (86 days after inoculation in experiment 1 and 67 days in experiment 2), the final population (Pf) of P. brachyurus was estimated and the reproductive factor (RF = Pf/Pi) was calculated. The results demonstrated that black oat (RF = 0.04-1.03) is more valuable than Algerian oat (RF = 2.63-2.88) or white oat (RF = 1.37-1.93) for the management of P. brachyurus.

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When building genetic maps, it is necessary to choose from several marker ordering algorithms and criteria, and the choice is not always simple. In this study, we evaluate the efficiency of algorithms try (TRY), seriation (SER), rapid chain delineation (RCD), recombination counting and ordering (RECORD) and unidirectional growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent LOD scores) and LHMC (likelihood through hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. A linkage map of a hypothetical diploid and monoecious plant species was simulated containing one linkage group and 21 markers with fixed distance of 3 cM between them. In all, 700 F(2) populations were randomly simulated with and 400 individuals with different combinations of dominant and co-dominant markers, as well as 10 and 20% of missing data. The simulations showed that, in the presence of co-dominant markers only, any combination of algorithm and criteria may be used, even for a reduced population size. In the case of a smaller proportion of dominant markers, any of the algorithms and criteria (except SALOD) investigated may be used. In the presence of high proportions of dominant markers and smaller samples (around 100), the probability of repulsion linkage increases between them and, in this case, use of the algorithms TRY and SER associated to RIPPLE with criterion LHMC would provide better results. Heredity (2009) 103, 494-502; doi:10.1038/hdy.2009.96; published online 29 July 2009