Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

Regression models for grouped survival data: Estimation and sensitivity analysis

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.

The exponentiated generalized gamma distribution with application to lifetime data

A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

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.

Storage as a tool to improve wood fuel quality

This work analysed the influence of storage in the quality of forest biomass for energy generation in the region of Lages, Brazil. Logs of Pinus taeda L. and Eucalyptus dunnii Maiden were harvested and piled during the four different seasons: spring, summer, fall and winter. The analyses were performed immediately after harvesting (without being stored), after two, four and six months of storage. The evaluated properties were: moisture content, gross and net calorific value, ash content and solubility in cold water, hot water and sodium hydroxide. The species composition, storage span, harvesting season and storage season influenced the forest biomass characteristics. In general, eucalyptus presented better results than pine, losing moisture faster, having less alteration in the chemical composition and producing greater energetic gain over storage time. For both species, the ideal storage time was four months. Furthermore, spring and summer were the best harvesting seasons. Thus, if the forest biomass is harvested at the end of winter or beginning of spring with subsequent storage during the summer, this biomass will have the best performance for energy production. (C) 2011 Elsevier Ltd. All rights reserved.

Evaluation of FAO Penman-Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada

Grass reference evapotranspiration (ETo) is an important agrometeorological parameter for climatological and hydrological studies, as well as for irrigation planning and management. There are several methods to estimate ETo, but their performance in different environments is diverse, since all of them have some empirical background. The FAO Penman-Monteith (FAD PM) method has been considered as a universal standard to estimate ETo for more than a decade. This method considers many parameters related to the evapotranspiration process: net radiation (Rn), air temperature (7), vapor pressure deficit (Delta e), and wind speed (U); and has presented very good results when compared to data from lysimeters Populated with short grass or alfalfa. In some conditions, the use of the FAO PM method is restricted by the lack of input variables. In these cases, when data are missing, the option is to calculate ETo by the FAD PM method using estimated input variables, as recommended by FAD Irrigation and Drainage Paper 56. Based on that, the objective of this study was to evaluate the performance of the FAO PM method to estimate ETo when Rn, Delta e, and U data are missing, in Southern Ontario, Canada. Other alternative methods were also tested for the region: Priestley-Taylor, Hargreaves, and Thornthwaite. Data from 12 locations across Southern Ontario, Canada, were used to compare ETo estimated by the FAD PM method with a complete data set and with missing data. The alternative ETo equations were also tested and calibrated for each location. When relative humidity (RH) and U data were missing, the FAD PM method was still a very good option for estimating ETo for Southern Ontario, with RMSE smaller than 0.53 mm day(-1). For these cases, U data were replaced by the normal values for the region and Delta e was estimated from temperature data. The Priestley-Taylor method was also a good option for estimating ETo when U and Delta e data were missing, mainly when calibrated locally (RMSE = 0.40 mm day(-1)). When Rn was missing, the FAD PM method was not good enough for estimating ETo, with RMSE increasing to 0.79 mm day(-1). When only T data were available, adjusted Hargreaves and modified Thornthwaite methods were better options to estimate ETo than the FAO) PM method, since RMSEs from these methods, respectively 0.79 and 0.83 mm day(-1), were significantly smaller than that obtained by FAO PM (RMSE = 1.12 mm day(-1). (C) 2009 Elsevier B.V. All rights reserved.

Distribution and storage characterization of soil solution for drip irrigation

The increased use of marginal quality water with drip irrigation requires sound fertigation practices that reconcile environmental concerns with viable crop production objectives. We conducted experiments to characterize dynamics and patterns of soil solution within wet bulb formed by drip irrigation. Time-domain reflectometry probes were used to monitor the distribution of potassium nitrate (KNO(3)) and water distribution from drippers discharging at constant flow rates of 2, 4 and 8 L h(-1) in soil-filled containers. Considering results from different profiles, we observed greater solute storage near the dripper decreasing gradually towards the wetting front. About half of the applied KNO(3) solution (48%) was stored in the first layer (0-0.10 m) for all experiments, 29% was stored in the next layer (0.10-0.20 m). Comparing different dripper flow rates, we observed higher solution storage for 4 L h(-1), with 45, 53 and 47% of applied KNO(3) solution accumulating in the first layer (0-0.10 m) for dripper flow rates of 2, 4 and 8 L h(-1), respectively. The results suggest that based on the volume and frequency used in this experiment, it would be advantageous to apply small amounts of solution at more frequent intervals to reduce deep percolation losses of applied water and solutes.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Nutritional Quality of Sorghum Seeds: Storage Proteins and Amino Acids

One sorghum commercial genotype (MASSA 03) and nine ICRISAT high-lysine genotypes from India were analyzed for storage protein content, distribution profile, and soluble amino acid concentrations. Storage proteins fraction were extracted and separated by SDS-PAGE. Soluble amino acids contents were determined by HPLC. Variations in intensity and appearance and disappearance of protein bands were observed among the sorghum genotypes suggesting genetic variability. Amino acid profile also indicated large variations in the amino acid concentrations. The high lysine and threonine soluble concentrations observed in the seeds of the sorghum genotypes encouraged the use of these genotypes as potential food source due to the better balanced amino acids profile.

Influence of egg pre-storage heating period and storage length on incubation results

This experiment aimed at evaluating the influence of different heating times of settable eggs of Cobb 500 (R) broiler breeders before submitting them to different storage periods on egg weight loss, embryo mortality, and hatchability. A total number of 1,980 eggs were distributed in a completely randomized experimental design with a 3 x 3 factorial arrangement, comprising nine treatments with 22 replicates of 10 eggs each. The following factors were analyzed: pre-storage heating periods (0, 6, 12 hours at 36.92 degrees C) and storage periods (4, 9, 14 days at 12.06 degrees C). After storage, eggs were incubated under usual conditions, and were transferred to the hatcher at 442 hours of incubation. Eggs were weighed before heating, incubation, and transference to determine weight loss. Partial hatchability was determined at 480 hours, and total hatchability at 498 hours of incubation. Embryo mortality was determined in non-hatched eggs. It was concluded that heating eggs for six hour before storage improves incubation results as it decreases incubation length and late embryo mortality, therefore its use can be indicated in commercial operations. Storing eggs for 14 days and pre-heating for 14 days and pre-heating for 12 hours severely impair incubation results, and therefore are not recommended.

Influence of egg pre-storage heating period and storage length on the digestive tract of newly-hatched broiler chicks

An experiment was carried out to evaluate the effect of different heating times of settable eggs of Cobb 500 (R) broiler breeders before submitting them to different storage periods on body weight, digestive tract organ weights, and intestinal mucosa morphology of newly-hatched chicks. Settable eggs were distributed in a completely randomized experimental design with a 3 x 3 factorial arrangement: pre-storage heating periods (0, 6, 12 hours at 36.92 degrees C) and storage periods (4, 9, 14 days at 12.06 degrees C). Body weight and relative weights of the yolk sac, heart, liver, proventriculus+gizzard, and intestinal segments were measured in chicks hatching at 480 and 498 hours of incubation. Villi height, width and perimeter, and crypt depth < im) were measured in duodenal histological sections. It was concluded that pre-storage healing for six hours of eggs stored for four or nine days increases small intestine weight of newly-hatched chicks, but does not influence the morphology of the duodenal mucosa. Pre-storage heating for 12 hours negatively influences body weight and duodenal mucosa development, and therefore this practice is not recommended. Storage length does not have consistent effect on body weight and development of the gastrointestinal tract.

Ethylene action blockade and cold storage affect ripening of `Golden` papaya fruit

The purpose of this work was to evaluate the effects of ethylene action blockade and cold storage on the ripening of `Golden` papaya fruit. Papayas harvested at maturity stage 1 (up to 15% yellow skin) were evaluated. Half of the fruits, whether treated or not treated with 100 nL L(-1) of 1-methylcyclopropene (1-MCP), were stored at 23A degrees C, while the other half were stored at 11A degrees C for 20 days prior to being stored at 23A degrees C. Non-refrigerated fruits receiving 1-MCP application presented a reduction in respiratory activity, ethylene production, skin color development and pectinmethylesterase activity. Even with a gradual increase in ethylene production at 23A degrees C, fruits treated with 1-MCP maintained a high firmness, but presented a loss of green skin color. Cold storage caused a decrease in ethylene production when fruits were transferred to 23A degrees C. The results suggest that pulp softening is more dependent on ethylene than skin color development, and that some processes responsible for loss of firmness do not depend on ethylene.

Drying and storage of cauliflower (Brassica oleracea var. botrytis) hydroprimed seeds

Literature has documented beneficial effects of seed priming on speed, synchronization and uniformity of germination. often leading to improved stand establishment. However. doubts still persist about the possible reversal effects, after drying and during storage of primed seeds that could overcome, partial or totally, the improved performance. The objectives of this research were to identify drying and storage procedures that would maintain the physiological performance achieved after seed priming, without negative effects on storability. First. hydroprimed cauliflower Seeds cv. Sharon and cv. Teresopolis Gigante, each represented by three seed lots were submitted to fast drying, slow drying, and treatments of pre-drying incubation (exposure to 35 degrees C, to a polyethylene glycol 6000 solution or a heat shock) followed by fast drying. In the second phase of this study, hydroprimed seed samples were submitted to fast drying (30-35 degrees C and 40-50% R.H.) and stored under laboratory conditions or in a chamber at 20 degrees C and 50% relative humidity for six months. Seed physiological potential was evaluated after 60-day intervals for germination (speed and percentage), Seedling emergence and saturated salt accelerated aging tests. All drying treatments efficiently preserved the favourable priming effects, except for the incubation at 35 degrees C for 96-144 hours. The beneficial priming effects followed by fast drying persisted for four months under controlled conditions (20 degrees C and 50% relative humidity).

CLIMATOLOGICAL HYDRIC BALANCE, EFFECTIVE SOIL WATER STORAGE AND TRANSPIRATION IN COFFEE CULTURE

The climatic water balance is one of the most used tools to assess, indirectly the amount of water present in the soil is capable of meeting the water needs of the plant. This study analyzed the climatologic hydric balance, the effective soil water storage and coffee plant transpiration in dry regimen cultivation. Daily climatologic hydric balance was calculated for coffee from January 2003 to May 2006. It was concluded that even in the most rainy months of the year, there is a hydric deficit in coffee plants grown in a dry regimen; effective soil water storage varied greatly through the years evaluated, and September was the most critical month, when this value remained below 30%; relative transpiration can not be taken as the single evaluation method for yield losses of coffee, grown in a dry regimen.

Soil Organic Carbon Stocks of Rio Grande do Sul, Brazil

Robust and accurate regional estimates of C storage in soils are currently an important research topic because of ongoing debate about human-induced changes in the terrestrial C cycle. Widely available geoprocessing tools were applied to estimate native soil organic C (SOC) stocks of Rio Grande do Sul state in southern Brazil to a depth of 30 cm from previously sampled soil pedons under undisturbed vegetation. The study used a statewide comprehensive soil survey comprising a small-scale soil map, a climate map, and a soil pedon database. Soil organic C stocks under native vegetation were calculated with two different approaches: the Tier 1 method of the Intergovernmental Panel on Climate Change (IPCC) and a refined method based on actual field measurements derived from soil profile data. Highest SOC stocks occurred in Neossolos Quartzarenico hidromorfico (Aquents), Organossolos Tiomorficos (Hemists), Latossolos Brunos (Udox), and Vertissolos Ebanicos (Uderts) soil classes. Before human use of soils, most C was stored in the Latossolos Vermelhos (Udox) and Neossolos Regoliticos (Orthents), which occupy a large area of Rio Grande do Sul. Generally, IPCC default reference SOC stocks compared well with SOC stocks calculated from soil pedons. The total SOC stock of Rio Grande do Sul was estimated at 1510.3 Tg C (5.8 kg C m(-2)) by the IPPC method and 1597.5 +/- 363.9 Tg C (7.4 +/- 1.9 kg C m(-2)) calculated from soil pedons. The SOC digital map and SOC database developed in this study provide crucial background information for state-level contemporary assessment of C stocks and soil C sequestration programs and initiatives.