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Abstract This study evaluated routine laboratory biomarkers (RLB) to predict the infectious bacterial group, Gram-positive (GP) or Gram-negative (GN) associated with bloodstream infection (BSI) before the result of blood culture (BC). A total of 13,574 BC of 6787 patients (217 BSI-GP and 238 BSI-GN) and 68 different RLB from these were analyzed. The logistic regression model was built considering BSI-GP or BSI-GN as response variable and RLB as covariates. After four filters applied total of 320 patients and 16 RLB remained in the Complete-Model-CM, and 4 RLB in the Reduced-Model-RM (RLB p > 0.05 excluded). In the RM, only platelets, creatinine, mean corpuscular hemoglobin and erythrocytes were used. The reproductivity of both models were applied to a test bank of 2019. The new model presented values to predict BSI-GN of the area under the curve (AUC) of 0.72 and 0.69 for CM and RM, respectively; with sensitivity of 0.62 and 0.61 (CM and RM) and specificity of 0.67 for both. These data confirm the discriminatory capacity of the new models for BSI-GN (p = 0.64). AUC of 0.69 using only 4 RLB, associated with the patient's clinical data could be useful for better targeted antimicrobial therapy in BSI.

Anthracnose (ANT) and angular leaf spot (ALS) are significant diseases in common bean, leading to considerable yield losses under specific environmental conditions. The California Dark Red Kidney (CDRK) bean cultivar is known for its resistance to multiple races of both pathogens. Previous studies have identified the CoPv01CDRK/PhgPv01CDRK resistance loci on chromosome Pv01. Here, we evaluated the expression levels of ten candidate genes near the CoPv01CDRK/PhgPv01CDRK loci and plant defense genes using quantitative real-time PCR in CDRK cultivar inoculated with races 73 of Colletotrichum lindemuthianum and 63-39 of Pseudocercospora griseola. Gene expression analysis revealed that the Phvul.001G246300 gene exhibited the most elevated levels, showing remarkable 7.8-fold and 8.5-fold increases for ANT and ALS, respectively. The Phvul.001G246300 gene encodes an abscisic acid (ABA) receptor with pyrabactin resistance, PYR1-like (PYL) protein, which plays a central role in the crosstalk between ABA and jasmonic acid responses. Interestingly, our results also showed that the other defense genes were initially activated. These findings provide critical insights into the molecular mechanisms underlying plant defense against these diseases and could contribute to the development of more effective disease management strategies in the future.

In explaining and forecasting real life scenarios, statistical distributions are very helpful. It is very important to select the best fitting statistical distribution for modelling data. In analysis of real world phenomena like in reliability and economics, we may find distributions for bounded data observed as percentages, proportions or fractions (see, for example, Marshall and Olkin (2007)). In this context, in view of pertinent transformation on the Gumbel Type-II model, we suggest and study the unit Gumbel Type-II (UG-TII) model and explore few of its statistical characteristics. We also consider various methods of estimating the unknown parameters of UG-TII model from the frequentist perspective. Monte Carlo simulations are worked out in order to compare efficiency of suggested estimation methods for small as well as large samples. The efficiency of estimators is measured using simulated samples in terms of their bias and mean square error. In the end, two datasets have been examined in attempt to validate the realistic possibilities of new model. In comparison to the six severe competitors.

Abstract The emergence of polymyxin resistance in Gram-negative bacteria infections has motivated the use of combination therapy. This study determined the mutant selection window (MSW) of polymyxin B alone and in combination with meropenem and fosfomycin against A. baumannii strains belonging to clonal lineages I and III. To evaluate the inhibition of in vitro drug resistance, we investigate the MSW-derived pharmacodynamic indices associated with resistance to polymyxin B administrated regimens as monotherapy and combination therapy, such as the percentage of each dosage interval that free plasma concentration was within the MSW (%TMSW) and the percentage of each dosage interval that free plasma concentration exceeded the mutant prevention concentration (%T>MPC). The MSW of polymyxin B varied between 1 and 16 µg/mL for polymyxin B-susceptible strains. The triple combination of polymyxin B with meropenem and fosfomycin inhibited the polymyxin B-resistant subpopulation in meropenem-resistant isolates and polymyxin B plus meropenem as a double combination sufficiently inhibited meropenem-intermediate, and susceptible strains. T>MPC 90% was reached for polymyxin B in these combinations, while %TMSW was 0 against all strains. TMSW for meropenem and fosfomycin were also reduced. Effective antimicrobial combinations significantly reduced MSW. The MSW-derived pharmacodynamic indices can be used for the selection of effective combination regimen to combat the polymyxin B-resistant strain.

Covariate-related response variables that are measured on the unit interval frequently arise in diverse studies when index and proportion data are of interest. A regression on the mean is commonly used to model this relationship. Instead of relying on the mean, which is sensitive to atypical data and less general, we can estimate such a relation using fractile regression. A fractile is a point on a probability density curve such that the area under the curve between that point and the origin is equal to a specified fraction. Fractile or quantile regression modeling has been considered for some statistical distributions. Our objective in the present article is to formulate a novel quantile regression model which is based on a parametric distribution. Our fractile regression is developed reparameterizing the initial distribution. Then, we introduce a functional form based on regression through a link function. The main features of the new distribution, as well as the density, distribution, and quantile functions, are obtained. We consider a brand-new distribution to model the fractiles of a continuous dependent variable (response) bounded to the interval (0, 1). We discuss an R package with random number generators and functions for probability density, cumulative distribution, and quantile, in addition to estimation and model checking. Instead of the original distribution-free quantile regression, parametric fractile regression has lately been employed in several investigations. We use the R package to fit the model and apply it to two case studies using COVID-19 and medical data from Brazil and the United States for illustration.

It is well known that the maximum likelihood estimates (MLEs) have appealing statistical properties. Under fairly mild conditions their asymptotic distribution is normal, and no other estimator has a smaller asymptotic variance. However, in finite samples the maximum likelihood estimates are often biased estimates and the bias disappears as the sample size grows. Mazucheli, Menezes, and Ghitany (2018b) introduced a two-parameter unit-Weibull distribution which is useful for modeling data on the unit interval, however its MLEs are biased in finite samples. In this paper, we adopt three approaches for bias reduction of the MLEs of the parameters of unit-Weibull distribution. The first approach is the analytical methodology suggested by Cox and Snell (1968), the second is based on parametric bootstrap resampling method, and the third is the preventive approach introduced by Firth (1993). The results from Monte Carlo simulations revealed that the biases of the estimates should not be ignored and the bias reduction approaches are equally efficient. However, the first approach is easier to implement. Finally, applications to two real data sets are presented for illustrative purposes.

The transformed family of distributions are sometimes very useful to explore additional properties of the phenomenons which non-transformed (baseline) family of distributions cannot. In this paper, we introduce a new transformed model, called the unit-Gompertz (UG) distribution which exhibit right-skewed (unimodal) and reversed-J shaped density while the hazard rate has constant, increasing, upside-down bathtub and then bathtub shaped hazard rate. Some statistical properties of this new distribution are presented and discussed. Maximum likelihood estimation for the parameters that index UG distribution are derived along with their corresponding asymptotic standard errors. Monte Carlo simulations are conducted to investigate the bias, root mean squared error of the maximum likelihood estimators as well as the coverage probability. Finally, the potentiality of the model is presented and compared with three others distributions using two real data sets.

The Vasicek distribution is a two-parameter probability model with bounded support on the open unit interval. This distribution allows for different and flexible shapes and plays an important role in many statistical applications, especially for modeling default rates in the field of finance. Although its probability density function resembles some well-known distributions, such as the beta and Kumaraswamy models, the Vasicek distribution has not been considered to analyze data on the unit interval, especially when we have, in addition to a response variable, one or more covariates. In this paper, we propose to estimate quantiles or means, conditional on covariates, assuming that the response variable is Vasicek distributed. Through appropriate link functions, two Vasicek regression models for data on the unit interval are formulated: one considers a quantile parameterization and another one its original parameterization. Monte Carlo simulations are provided to assess the statistical properties of the maximum likelihood estimators, as well as the coverage probability. An R package developed by the authors, named vasicekreg, makes available the results of the present investigation. Applications with two real data sets are conducted for illustrative purposes: in one of them, the unit Vasicek quantile regression outperforms the models based on the Johnson-SB, Kumaraswamy, unit-logistic, and unit-Weibull distributions, whereas in the second one, the unit Vasicek mean regression outperforms the fits obtained by the beta and simplex distributions. Our investigation suggests that unit Vasicek quantile and mean regressions can be of practical usage as alternatives to some well-known models for analyzing data on the unit interval.

This study was performed to evaluate the effects of supplementation of lactating Nelore cows with calcium salts of long-chain fatty acids (Ca-LCFA) of soybean oil on in vitro oocytes competency, cleavage rate, embryo production rate, pregnancy rate, and sex ratio of transferred embryos. Fifteen multiparous Nelore cows grazed on a Tifton 85 pasture were allotted to two treatments: (1) supplement without fat inclusion (CONT, n = 6) and (2) supplement containing 47.2 g Ca-LCFA /kg (to provide an intake of 0.2 kg Ca-LCFA/day) based on dry matter (n = 9). Animals were subjected to 2.53 ± 1.35 rounds of consecutive ovum pick up at intervals of 27.65 ± 21.72 days. Oocytes were morphologically evaluated, selected, maturated, fertilized, and cultivated for embryo production in vitro and then transferred into recipients who had previously undergone an embryo transfer protocol at a fixed time. The number of aspirated oocytes, the proportion of viable oocytes, cleavage rate, embryo percentage, pregnancy rate, and sex ratio were not affected when Nelore cows were supplemented with Ca-LCFA of soybean oil compared with non-supplemented Nelore cows. In conclusion, our results suggest that feeding a supplement containing 47.2 g Ca-LCFA/kg (to provide an intake of 0.2 kg Ca-LCFA/day) to Nelore cows does not affect in vitro embryo production in lactating Nelore cows. However, further studies using higher dietary doses of fat could be useful to determine the potential of fat supplementation to improve in vitro embryo production.

The aim of this study was to model the individual height and volume of eucalyptus wood in two integrated crop-livestock-forest systems (ICLF1 and ICLF2) in Campo Grande, a city in the state of Mato Grosso do Sul, Brazil. Classic nonlinear growth models were adjusted for height (Logistic, Gompertz, Richards, Weibull, Van Bertalanffy, Brody, Mitscherlich, and Chapman and Richards) and volume (Shumacher-hall nonlinear, Takata, Honner, Logistic, Gompertz, and Weibull) in two structural arrangements: ICLF1, with a spacing of 14 x 2 m and density of 357 trees ha-1, and ICLF2, with a spacing of 22 x 2 m and density of 227 trees ha-1. Diameter at Breast Height (DBH) measurements were performed in 100% of trees, with measurements of the total height of some individuals and a rigorous scaling procedure in diameter classes. According to the calculated value of Student's t-test, there was no significant evidence that DBH and the average height of the trees were different between ICLF1 and ICLF2. Based on the Akaike information criterion (AIC), the corrected Akaike information criterion (AICC) and the Bayesian information criterion (BIC), the Richards model was selected to estimate heights and the Takata model was selected to estimate the volume.

Quantile regression provides a framework for modeling the relationship between a response variable and covariates using the quantile function. This work proposes a regression model for continuous variables bounded to the unit interval based on the unit Birnbaum–Saunders distribution as an alternative to the existing quantile regression models. By parameterizing the unit Birnbaum–Saunders distribution in terms of its quantile function allows us to model the effect of covariates across the entire response distribution, rather than only at the mean. Our proposal, especially useful for modeling quantiles using covariates, in general outperforms the other competing models available in the literature. These findings are supported by Monte Carlo simulations and applications using two real data sets. An R package, including parameter estimation, model checking as well as density, cumulative distribution, quantile and random number generating functions of the unit Birnbaum–Saunders distribution was developed and can be readily used to assess the suitability of our proposal.

ABSTRACT This study was conducted to evaluate the effects of long-chain fatty acid soaps (LCFAS) of soybean oil on the production and quality of aspirated cumulus-oocyte complexes (COC) of lactating Nellore (Bos taurus indicus) cows. The effects of LCFAS on the plasma concentration of lipoproteins, total cholesterol, triacylglycerol, urea N, and insulin were also addressed. Thirty lactating Nellore cows were randomly assigned to one of two dietary groups. Cows were grazed on a Tifton 85 pasture throughout the experiment (100 days). Treatments consisted of a supplement with no fat included (CONT); and a supplement containing 47.2 g/kg of LCFAS on a dry matter basis. After 14 days of treatment, animals were subjected to 4.93±1.55 rounds of consecutive ovum pickup (OPU) at intervals of 21.71±11.76 days. Blood samples were collected from all cows throughout the experiment at 25-day intervals (four samples per cow). Cows that were fed LCFAS supplements and cows that were fed CONT supplements had similar numbers of total aspirated oocytes (viable and not viable) by OPU and grades of viable oocytes. Plasma concentrations of high-density lipoprotein (HDL) were increased in cows supplemented with LCFAS. Plasma concentrations of LDL and total cholesterol were increased by LCFAS supplementation after 50 days on dietary treatment and insulin concentration was increased from 75 days on treatment. Long-chain fatty acid soaps from soybean oil added at 47.2 g/kg have no effect on the number of aspirated COC or their quality in Nellore lactating cows even with changes in plasma concentration of HDL, LDL, total cholesterol, and insulin. Thus, this supplementation has no benefits when the main objective is to improve oocyte production and quality.

Using the number of thrips found in the maize seedlings from a longitudinal study, in this work a regression analysis was conducted through polynomial models and nonlinear logistic, under the assumption of homoscedasticity and multiplicative heteroscedasticity of variances. The response variable represents the number of thrips in adult phase observed in an entirely randomized trial involving 4 ground cover systems (tumbled oat, desiccated oat, mowed oat and incorporated oat), 8 replications with portions of 57.6 m2 and evaluated at 7, 11, 16, 23 and 31 days after the seedlings emergence. The parameters from the adopted models (homoscedastic and heteroscedastic) were estimated by maximizing the logarithm of the verisimilitude function. The adjusted model, via maximum verisimilitude, under the assumption of heteroscedasticity of the variances, did not over estimate the true asymptotic average number of thrips.

This paper presents estimates for the parameters included in long-term mixture and non-mixture lifetime models, applied to analyze survival data when some individuals may never experience the event of interest. We consider the case where the lifetime data have a three-parameter Burr XII distribution, which includes the popularWeibull mixture model as a special case. Classical and Bayesian procedures are used to get point estimates and confidence intervals for the unknown parameters. We consider a general survival model where the scale and shape parameters of the Burr XII distribution are dependent of some covariates. To illustrate the proposed methodology, we consider an application considering a leukaemia data set where the proposed model gives better fit for the data when compared to other existing models.

Foram estimados os componentes de variância para produção de leite e avaliado o impacto do aumento do número de animais na matriz de parentesco sobre os componentes de variância usando os métodos de Máxima Verossimilhança Restrita (REML) e Bayesiano via amostragem de Gibbs (GS). Utilizaram-se registros de produção de leite de vacas da raça Holandesa dos estados de Minas Gerais, São Paulo, Paraná, Santa Catarina e Rio Grande do Sul. Para cada estado, foram analisados dois conjuntos de dados: no primeiro, pedigree restrito, a matriz de parentesco foi constituída dos animais do respectivo estado; e, no segundo, pedigree completo, foram incluídos na matriz de parentesco os animais de todos os estados. Utilizou-se um modelo animal que incluiu os efeitos da estação de parto, rebanho-ano, grupo genético, ordem de parto e os efeitos genéticos aditivos e de ambiente permanente. As estimativas REML dos componentes de variância e de herdabilidade em todos os estados, obtidas com o pedigree restrito e com pedigree completo, foram similares. As estimativas REML de herdabilidade em Minas Gerais, São Paulo, Paraná, Santa Catarina e Rio Grande do Sul foram 0,19; 0,18; 0,26; 0,43 e 0,48, respectivamente. Houve fortes evidências de que as estimativas Bayesianas da variância genética com o PEDA foram superiores àquelas obtidas utilizando o PEDR. As herdabilidades e os desvios-padrão obtidos pelo método Bayesiano em Minas Gerais, São Paulo, Paraná, Santa Catarina e Rio Grande do Sul utilizando os pedigrees restrito e completo foram 0,21 ± 0,032 e 0,40 ± 0,025; 0,20 ± 0,017 e 0,27 ± 0,017; 0,28 ± 0,014 e 0,31 ± 0,014; 0,42 ± 0,041 e 0,56 ± 0,021; e 0,43 ± 0,039 e 0,55 ± 0,019, respectivamente. A variância genética aumentou significativamente em cada estado quando os animais dos outros estados foram incorporados na matriz de parentesco. Os menores desvios-padrão e intervalos de credibilidade dos componentes de variância foram estimados nos estados com maior número de lactações e sugerem que a precisão dos componentes de variância foi maior para esses estados.Variance components (VC) for milk yield of Holstein cows were estimated and the effects of increasing of the number of animals in the numerator relationship matrix (NRM) were evaluated on VC estimates obtained by REML and Bayesian inference via Gibbs sampling (GS). Data were obtained from herds in the states of Minas Gerais, São Paulo, Paraná, Santa Catarina, and Rio Grande do Sul. Two data sets were created for each state. In the first set, the NRM included only the pedigree of the animals of the state under consideration (PEDR). In the second, the NRM included animals from the five states (PEDA). An animal model including the effects of herd-year, parity, season, genetic group, effects of additive genetic and permanent environment was used. The REML estimates of VC and heritability in each state obtained from PEDR and PEDA were similar. The heritability in Minas Gerais, São Paulo, Paraná, Santa Catarina, and Rio Grande do Sul was 0.19, 0.18, 0.26, 0.43, and 0.48, respectively. There was evidence that the posterior means of the genetic variance of PEDA analyses were significantly greater than PEDR. Heritability and standard deviations estimated by GS in Minas Gerais, São Paulo, Paraná, Santa Catarina, and Rio Grande do Sul, using PEDR (PEDA), were 0.21 ± 0.032 (0.40 ± 0.025), 0.20 ± 0.017 (0.27 ± 0.017), 0.28 ± 0.014 (0.31 ± 0.014), 0.42 ± 0.041 (0.56 ± 0.021) and 0.43 ± 0.039 (0.55 ± 0.019), respectively. The genetic variance of each state increased significantly when animals from the other states were incorporated in its NRM. The smallest standard deviations and VC credibility intervals were estimated in the states with more records, which suggested that the precision of the VC estimates was higher in those states.

Os efeitos, sobre a avaliação genética da interação reprodutor-região, foram investigados analisando-se 108.702 registros de produção de leite (PL305) de vacas da raça Holandesa, pertencentes a rebanhos de Minas Gerais, São Paulo, Paraná, Sanata Catarina eRio Grande do Sul. Um modelo animal multicarácter foi aplicado para estimar os componentes de variância e covariância utilizando amostragem de Gibbs. As médias a posteriori da variância genética de Santa Catarina e Rio Grande do Sul foram superiores (p < 0,001) às estimadas nos demais Estados e iguais (p > 0,05) entre si. As herdabilidades variaram entre 0,24 e 0,38. As correlações genéticas entre os Estados foram de baixa magnitude e variaram entre 0,07 a 0,33. Os valores de correlação de Spearman entre os valores genéticos dos reprodutores variaram entre 0,73 e 0,86. Os resultados sugerem aexistência da interação genótipo-ambiente para PL305 entre os Estados de Minas Gerais, São Paulo, Paraná e os Estados de Santa Catarina e Rio Grande do Sul.The effects of sire-environment interaction on genetic evaluation were investigated by analyzing 108,702 records of milk yield (305ME) of Holstein cows from the states of Minas Gerais, São Paulo, Paraná, Santa Catarina and Rio Grande do Sul. A Multivariate animal model was applied to estimate of genetic variance and covariance components, using Gibbs sampling. The a posteriori means of genetic variance in Santa Catarina and Rio Grande do Sul were higher (p < 0.001) than estimates in others states, even though the estimates did not vary (p > 0.05) between these two states. Heritability estimates of states ranged from 0.24 to 0.38. Genetic correlations among states were low and ranged from 0.07 to 0.33. Spearman’s correlation among sire breeding values ranged from 0.73 to 0.86. These results suggest sire-environment interaction for 305ME in the states of Minas Gerais, São Paulo, Paraná and between the states of Santa Catarina and Rio Grande do Sul.

Registros de produção de leite ajustados para 305 dias de lactação (PL305) em vacas da raça Holandesa que pariram entre 1980 e 1993 foram utilizados para investigar a existência de heterogeneidade de variância e a interação genótipo × ambiente. Supondo-se variâncias heterogêneas, as PL305 nos estados de Minas Gerais, São Paulo, Paraná, Santa Catarina e Rio Grande do Sul foram tratadas como características diferentes. Admitindo-se homogeneidade de variância, a PL305 foi analisada segundo um modelo unicaracter. Os componentes de (co)variância e os parâmetros genéticos foram estimados utilizando-se métodos Bayesianos, via amostrador de Gibbs (GS), sob um modelo animal que incluiu os efeitos fixos de estação de parto, grupo genético, ordem de parição e classes rebanho-ano de parto e os efeitos genéticos aditivos e de ambiente permanente. A monitoração de convergência das distribuições das cadeias foi realizada pelo método de Heidelberg & Welch (1983). As estimativas dos componentes de variância e de herdabilidade foram obtidas com grande precisão na análise unicaracter. A média e o desvio-padrão (DP) a posteriori da herdabilidade foram 0,278±0,012. Na análise multicaracter, as estimativas mais precisas da (co)variância genética foram as obtidas em São Paulo e Paraná. As médias e os desvios-padrão a posteriori de herdabilidade para Minas Gerais, São Paulo, Paraná, Santa Catarina e Rio Grande do Sul, foram 0,280±0,021, 0,233±0,015, 0,280±0,012, 0,393±0,026 e 0,382±0,022, respectivamente. A baixa magnitude das correlações genéticas entre os estados (0,070 a 0,364) sugere a existência da interação genótipo × ambiente, logo, as PL305 em cada estado devem ser tratadas como características diferentes. O maior valor de correlação genética foi encontrado em São Paulo e Paraná. As variâncias genética e residual para PL305 foram significativamente diferentes entre a maioria dos estados.Adjusted for 305 days milk yield records of Holstein cows calving from 1980 to 1993 in the states of MG, SP, PR, SC, and RS were used to investigate heterogeneity of variance and to evaluate the genotype by environment interaction. Milk production from each State was considered as a different trait and variances were assumed heterogeneous. Milk production was also analyzed using a single-trait model assuming homogeneity of variance. (Co)variance components and genetic parameters were estimated by Bayesian inference, via Gibbs sampler (GS), using a model which included season of calving, genetic group, herd-year of calving and parity as fixed effects and animal additive genetic, permanent environmental and residual as random effects. Convergence of the GS chain to the stationary distribution was diagnosed using the method described by Heidelberg & Welch (1983). The posterior precision of the variance components and the heritability were high in the single-trait analysis. Posterior mean and standard deviation (SD) of heritability of milk yield were 0,278±0,012. For the multiple-trait analysis, posterior precisions of the (co)variance components were larger for SP and PR states. Posterior means and standard errors of heritability for MG, SP, PR, SC, and RS were 0.280±0.021, 0.233±0.015, 0.280±0.012, 0.393±0.026, and 0.382±0.022, respectively. Genetic correlations for milk yield between the five states were very low and ranged from 0.070 to 0.364, suggesting the presence of genotype by environment interaction. Differences in genetic and residual variances of milk yield among the states indicate it would be necessary to account for heterogeneous variances in genetic evaluations.

Um dos problemas mais comuns em estatística consiste em testar a hipótese H0 : µ= µ0 versus a alternativa H1 : µ≠ µ0 , em que µ0 é algum valor específico do parâmetro µ. A partir de uma amostra aleatória, sob a suposição de que a mesma é proveniente de uma distribuição Normal com média µ e desvio padrão Σ, ambos desconhecidos, pode-se aplicar o bem conhecido teste t-Student. Como alternativa, sob a suposição de simetria da dis-tribuição dos dados, pode-se utilizar o teste não-paramétrico conhecido na literatura como tes-te de Wilcoxon (Conover, 1971). Neste artigo, é conduzido um estudo de simula-ção Monte-Carlo com o intuito de avaliar o tamanho e o poder dos testes t-Student e de Wilcoxon sob diferentes instâncias. Para o cálculo do tama-nho de ambos os testes, foram realizadas B = 100.000 simulações Monte-Carlo com 10 diferentes tamanhos de amostras, n = 10, 20, K , 90, 100. Cada uma das B = 100.000 amostras foram geradas das distribuições Normal, Laplace, Uniforme, t-Student e Logística sob a hipótese nula, sem perda de generalizades, com µ = 0. Para o cálculo do poder, novamente B = 100.000 amostras foram geradas sob a hipótese alternativa com µ0 = -1.0, -0.9, K , 0.9, 1.0

Um dos problemas mais comuns em estatística consiste em testar a hipótese H0 : m =m0 versus a alternativa H1 : m ¹m0 , em que m0 é algum valor específico do parâmetro m . A partir de uma amostra aleatória, sob a suposição de que a mesma é proveniente de uma distribuição Normal com média m e desvio padrão s , ambos desconhecidos, pode-se aplicar o bem conhecido teste t-Student. Como alternativa, sob a suposição de simetria da distribuição dos dados, pode-se utilizar o teste não-paramétrico conhecido na literatura como teste de Wilcoxon (Conover, 1971). Neste artigo, é conduzido um estudo de simulação Monte-Carlo com o intuito de avaliar o tamanho e o poder dos testes t-Student e de Wilcoxon sob diferentes instâncias. Para o cálculo do tamanho de ambos os testes, foram realizadas B = 100 .000 simulações Monte-Carlo com 10 diferentes tamanhos de amostras, n = 10, 20, ... , 90, 100. Cada uma das B = 100 .000 amostras foram geradas das distribuições Normal, Laplace, Uniforme,t-Student e Logística sob a hipótese nula, sem perda de generalizades, com m = 0. Para o cálculo do poder, novamente B = 100.000 amostras foram geradas sob a hipótese alternativa com 1.0, 0.9, ,0.9,1.0 0 m = - - K .A typical problem in statistics data analysis consists in testing a null hypothesis H0 : m =m0 versus an alternative H1 : m ¹m0 , where m0 is some specific value of the true parameter m . From a randomsample with normal distribution with mean m and variance s 2 , both unknown, we might use the well known t-student test. As an alternative to the usual t-student test, under the symmetric supposition, we can use the nonparametric Wilcoxon on test (Conover, 1971). In this paper, a Monte-Carlo simulation study was conducted to calculate the empirical size and power of the t-student and Wilcoxon tests. In this study, several instances were considered. For the size of both tests, we considered sample sizes equal to n=10,20,K,90,100 simulated from Normal, Laplace, Uniform, t-Student and Logistic distributions, under the null hypothesis with m = 0 . In the power study, from the same sample sizes and for all distributions, random samples were simulated from the alternative hypothesis consideringm 0 = -1.0,-0.9,K, 0.9,1.0 .

Diferente dos modelos de regressão lineares, em que a qualidade e principalmente a validade do ajuste são simplesmente avaliadas por meio de diagnósticos de regressão, no caso não linear, além de diagnósticos usuais, outros procedimentos devem ser seguidos. Esses procedimentos, particulares dos modelos de regressão não lineares, são úteis na avaliação da extensão do comportamento não-linear. Modelos não-lineares com comportamento distante do comportamento linear podem ter seus resultados assintóticos invalidados, principalmente em situações em que pequenas amostras são disponíveis. Considerando a importância de se avaliar a extensão do comportamento não-linear de modelos de regressão não-lineares, neste artigo são apresentadas as principais medidas de não-linearidade discutidas na literatura. Em particular, consideram-se as Medidas de Curvatura de Bates e Watts, a Medida de Vício de Box, Estudo de Simulação e Medidas de Assimetria.

In many applications of lifetime data analysis, it is important to perform inferences about the change-point of the hazard function. The change-point could be a maximum for unimodal hazard functions or a minimum for bathtub forms of hazard functions and is usually of great interest in medical or industrial applications. For lifetime distributions where this change-point of the hazard function can be analytically calculated, its maximum likelihood estimator is easily obtained from the invariance properties of the maximum likelihood estimators. From the asymptotical normality of the maximum likelihood estimators, confidence intervals can also be obtained. Considering the exponentiated Weibull distribution for the lifetime data, we have different forms for the hazard function: constant, increasing, unimodal, decreasing or bathtub forms. This model gives great flexibility of fit, but we do not have analytic expressions for the change-point of the hazard function. In this way, we consider the use of Markov Chain Monte Carlo methods to get posterior summaries for the change-point of the hazard function considering the exponentiated Weibull distribution.

Os efeitos, sobre a avaliação genética da interação reprodutor-região, foram investigados analisando-se 108.702 registros de produção de leite (PL305) de vacas da raça Holandesa, pertencentes a rebanhos de Minas Gerais, São Paulo, Paraná, Sanata Catarina e Rio Grande do Sul. Um modelo animal multicarácter foi aplicado para estimar os componentes de variância e covariância utilizando amostragem de Gibbs. As médias a posteriori da variância genética de Santa Catarina e Rio Grande do Sul foram superiores (p < 0,001) às estimadas nos demais estados e iguais (p > 0,05) entre si. As herdabilidades variaram entre 0,24 e 0,38. As correlações genéticas entre os estados foram de baixa magnitude e variaram entre 0,07 a 0,33. Os valores de correlação de Spearman entre os valores genéticos dos reprodutores variaram entre 0,73 e 0,86. Os resultados sugerem a existência da interação genótipo-ambiente para PL305 entre os estados de Minas Gerais, São Paulo, Paraná e os estados de Santa Catarina e Rio Grande do Sul.

Os anestésicos locais são as drogas mais utilizadas na Odontologia. São utilizados com freqüência na clínica cirúrgica, sendo de grande ajuda para o cirurgião, visto que a dor tem sido descrita como uma experiência desagradável, tanto em nível sensorial quanto psicológico. O objetivo deste estudo foi adquirir mais conhecimento a respeito da articaína a 4% com adrenalina (Articaine®), além de compará-la clinicamente com a prilocaína 3% com felipressina (Prilonest®). Os anestésicos foram administrados em 21 cirurgias, nas quais, em 8, utilizou-se articaína e, em 13, prilocaína, para remoção de terceiros molares semi-retidos, superior e inferior. Como medicação pré-cirúrgica, foram administradas, uma hora antes, 4 mg de Dexametasona e, no pós-operatório, Dipirona 500 mg, 35 gotas, em caso de necessidade. Foram registrados tempo de latência, duração da cirurgia, duração de efeito do anestésico, efeitos colaterais e quantidade de analgésicos consumidos. Os dados referentes à articaína mostraram-se semelhantes aos encontrados na literatura.

In its standard form, a lifetime regression model usually assumes that the time until an event occurs has a constant shape parameter and a scale parameter that is a function of covariates. In this paper we consider lifetime models with shape parameter dependent on a vector of covariates. Two special models are considered, the Weibull model and a mixture model incorporating long-term survivors, when we consider that the incidence probability is also dependent on covariates. Classical parameters estimation approach is considered on two real data sets.

Resumo Este trabalho teve como objetivo avaliar o desempenho da distribuição Nakagami na análise de séries de precipitação mensal, ao longo de vários anos, visando à seleção de uma distribuição útil para o planejamento e gestão de atividades dependentes dos índices de precipitação na Região Sul do Brasil. Para tanto, compara-se a mesma com cinco distribuições alternativas: Weibull, Gama, Log-Normal, Log-Logística e Inversa-Gaussiana. Foram utilizadas séries históricas de 33 estações meteorológicas observadas entre janeiro de 1970 a dezembro de 2014, totalizando 396 séries (33 estações × 12 meses). Para a escolha da distribuição, que forneceu o melhor ajuste, foram utilizados os valores dos critérios de informação de Akaike, de Kolmogorov-Smirnov, de Anderson-Darling e de Cramér-von Mises. Segundo estes critérios se encontrou que as distribuições Nakagami e Weibull foram selecionadas o maior número de vezes (Nakagami: 146 vezes e Weibull: 100 vezes). Embora a distribuição Nakagami não seja muito utilizada, na descrição de dados de precipitação, recomenda-se sua utilização na descrição do comportamento da pluviosidade mensal como alternativa para distribuições tradicionalmente utilizadas.