The Kumaraswamy Weibull distribution with application to failure data

For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Bias-corrected Pearson estimating functions for Taylor`s power law applied to benthic macrofauna data

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.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

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.

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.

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.

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.

Genetic population data of 12 STR loci of the PowerPlex (R) Y system in the state of Sao Paulo population (Southeast of Brazil)

Allele frequency distributions and population data for 12 Y-chromosomal short tandem repeats (STRs) included in the PowerPlex (R) Y Systems (Promega) were obtained for a sample of 200 healthy unrelated males living in S (a) over tildeo Paulo State (Southeast of Brazil). A total of 192 haplotypes were identified, of which 184 were unique and 8 were found in 2 individuals. The average gene diversity of the 12 Y-STR was 0.6746 and the haplotype diversity was 0.9996. Pairwise analysis confirmed that our population is more similar with the Italy, North Portugal and Spain, being more distant of the Japan. (c) 2007 Elsevier Ireland Ltd. All rights reserved.

Effects of light intensity and dilution rate on the semicontinuous cultivation of Arthrospira (Spirulina) platensis. A kinetic Monod-type approach

Semicontinuous cultures were carried out at different dilution rates (D) and light intensities (I) to determine the maximum productivity of Arthrospira platensis cultivated in helicoidal photobioreactor up to the achievement of pseudo-steady-state conditions. At I = 108 mu mol photons m(-2) s(-1), the semicontinuous regime ensured the highest values of maximum cell concentration (X(m) = 5772 +/- 113 mg L(-1)) and productivity (P(XS) = 1319 +/- 25 mg L(-1) d(-1)) at the lowest (D = 0.1 day(-1)) and the highest (D = 0.3 day(-1)) dilution rates, respectively. A kinetic model derived from that of Monod was proposed to determine the relationship between the product of light intensity to dilution rate (ID) and the cell productivity, which were shown to exert a combined influence on this parameter. This result put into evidence that pseudosteady-state conditions could be modified according to circumstances, conveniently varying one or other of the two independent variables. (C) 2010 Elsevier Ltd. All rights reserved.

Adsorption of Ni(2+), Zn(2+) and Pb(2+) onto dry biomass of Arthrospira (Spirulina) platensis and Chlorella vulgaris. I. Single metal systems

Adsorption of Ni(2+), Zn(2+) or Pb(2+) by dry biomass of Arthrospira (Spirulina) platensis and Chlorella vulgaris was studied as a function of contact time and initial metal concentration. The zero point of charge calculated for these biosorbents (pH(zpc) 4.0 and 3.4, respectively) and additional pH tests suggested the use of pH in the range 5.0-5.5 for the experiments. The equilibrium isotherms were evaluated in terms of maximum sorption capacity and sorption affinity. The pseudo first and second order kinetic models were considered to interpret the experimental data, and the latter best described the adsorption system. Both the Freundlich and Langmuir models were shown to well describe the sorption isotherms, thus suggesting an intermediate mono/multilayer sorption mechanism. Compared to A. platensis (q(e) = 0.354, 0.495 and 0.508 mmol g(-1) for Ni(2+), Pb(2)+ and Zn(2+), respectively), C. vulgaris behaved as a better biosorbent because of higher equilibrium sorption capacity (q(e) = 0.499, 0.634 and 0.664 mmol g(-1), respectively). The removal efficiency decreased with increasing metal concentration, pointing out a passive adsorption process involving the active sites on the surface of the biomasses. The FT-IR spectroscopy evidenced that ions removal occurred mainly by interaction between metal and carboxylate groups present on both the cell walls. (C) 2011 Elsevier B.V. All rights reserved.

Kinetic and thermodynamic investigation on clavulanic acid formation and degradation during glycerol fermentation by Streptomyces DAUFPE 3060

Clavulanic acid (CA) is a potent inhibitor of beta-lactamases, produced by some resistant pathogenic microorganisms, which allows efficient treatment of infectious diseases. The kinetic and thermodynamic parameters of CA production by a new isolate of Streptomyces DAUFPE 3060 and its degradation were evaluated. The effect of temperature on the system was investigated in the range 24-40 degrees C adopting an overall model accounting for (a) the Arrhenius-type formation of CA by fermentation, (b) the hypothetical reversible unfolding of the enzyme limiting the overall metabolism, and (c) the irreversible first-order degradation of CA. The higher rates of CA formation (k(CA) = 0,107 h(-1)) and degradation (k(d) = 0.062 h(-1)) were observed at 32 and 40 degrees C, respectively. The main thermodynamic parameters of the three above hypothesized events were estimated. In particular, the activation parameters of degradation (activation energy = 39.0 kJ/mol; Delta H(d)* = 36.5 kJ/mol; Delta S(d)* = -219.7 J/(mol K); Delta G(d)* = 103.5 kJ/mol) compare reasonably well with those reported in the literature for similar system without taking into account the other two events. (C) 2009 Elsevier Inc. All rights reserved.

Stability of clavulanic acid under variable pH, ionic strength and temperature conditions. A new kinetic approach

Clavulanic acid (CA) is a beta-lactam antibiotic that alone exhibits only weak antibacterial activity, but is a potent inhibitor of beta-lactamases enzymes. For this reason it is used as a therapeutic in conjunction with penicillins and cephalosporins. However, it is a well-known fact that it is unstable not only during its production phase, but also during downstream processing. Therefore, the main objective of this study was the evaluation of CA long-term stability under different conditions of pH and temperature, in the presence of variable levels of different salts, so as to suggest the best conditions to perform its simultaneous production and recovery by two-phase polymer/salt liquid-liquid extractive fermentation. To this purpose, the CA stability was investigated at different values of pH (4.0-8.0) and temperature (20-45 degrees C), and the best conditions were met at a pH 6.0-7.2 and 20 degrees C. Its stability was also investigated at 30 degrees C in the presence of NaCl, Na(2)SO(4), CaCl(2) and MgSO(4) at concentrations of 0.1 and 0.5 M in Mcllvaine buffer (pH 6.5). All salts led to increased CA instability with respect to the buffer alone, and this effect decreased in following sequence: Na(2)SO(4) > MgSO(4) > CaCl(2) > NaCl. Kinetic and thermodynamic parameters of CA degradation were calculated adopting a new model that took into consideration the equilibrium between the active and a reversibly inactivated form of CA after long-time degradation. (C) 2009 Elsevier B.V. All rights reserved.

Brazilian Network of Food Data Systems and LATINFOODS Regional Technical Compilation Committee: Food composition activities (2006-2009)

The Brazilian Network of Food Data Systems (BRASILFOODS) has been keeping the Brazilian Food Composition Database-USP (TBCA-USP) (http://www.fcf.usp.br/tabela) since 1998. Besides the constant compilation, analysis and update work in the database, the network tries to innovate through the introduction of food information that may contribute to decrease the risk for non-transmissible chronic diseases, such as the profile of carbohydrates and flavonoids in foods. In 2008, data on carbohydrates, individually analyzed, of 112 foods, and 41 data related to the glycemic response produced by foods widely consumed in the country were included in the TBCA-USP. Data (773) about the different flavonoid subclasses of 197 Brazilian foods were compiled and the quality of each data was evaluated according to the USDAs data quality evaluation system. In 2007, BRASILFOODS/USP and INFOODS/FAO organized the 7th International Food Data Conference ""Food Composition and Biodiversity"". This conference was a unique opportunity for interaction between renowned researchers and participants from several countries and it allowed the discussion of aspects that may improve the food composition area. During the period, the LATINFOODS Regional Technical Compilation Committee and BRASILFOODS disseminated to Latin America the Form and Manual for Data Compilation, version 2009, ministered a Food Composition Data Compilation course and developed many activities related to data production and compilation. (C) 2010 Elsevier Inc. All rights reserved.