New Flexible Regression Models Generated by Gamma Random Variables with Censored Data

We propose and study a new log-gamma Weibull regression model. We obtain explicit expressions for the raw and incomplete moments, quantile and generating functions and mean deviations of the log-gamma Weibull distribution. We demonstrate that the new regression model can be applied to censored data since it represents a parametric family of models which includes as sub-models several widely-known regression models and therefore can be used more effectively in the analysis of survival data. We obtain the maximum likelihood estimates of the model parameters by considering censored data and evaluate local influence on the estimates of the parameters by taking different perturbation schemes. Some global-influence measurements are also investigated. Further, for different parameter settings, sample sizes and censoring percentages, various simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We demonstrate that our extended regression model is very useful to the analysis of real data and may give more realistic fits than other special regression models

Some Extended Classes of Distributions: Characterizations and Properties

Based on a simple relationship between two truncated moments and certain functions of the th order statistic, we characterize some extended classes of distributions recently proposed in the statistical literature, videlicet Beta-G, Gamma-G, Kumaraswamy-G and McDonald-G. Several properties of these extended classes and some special cases are discussed. We compare these classes in terms of goodness-of-fit criteria using some baseline distributions by means of two real data sets

Produtividade da cenoura em função da qualidade da água e condicionador de solo no Vale do São Francisco.

O experimento foi conduzido no Campo Experimental da Caatinga, Embrapa Semi-Árido em Petrolina - PE, no primeiro semestre de 1998 com o objetivo de avaliar o efeito de diferentes níveis de salinidade da água de irrigação e do condicionador de solo na produtividade de cenoura, cultivar Brasília. O delineamento experimental foi de blocos ao acaso com seis tratamentos e quatro repetições. Os tratamentos foram: água com condutividade elétrica de 0,1dS/m (água do rio São Francisco - testemunha), 4,0 e 8,0 dS/m e água com condutividade elétrica 0,1; 4,0 e 8,0 dS/m mais condicionador de solo. As produtividades da cenoura variaram de 33,1 a 82,3 t/ha para os tratamentos irrigados com água salina mais condicionador de solo e água do rio São Francisco, respectivamente. Não se verificou diferença significativa na produtividade quando o uso de água do São Francisco (0,1dS/m) comparado à água com condutividade elétrica de 4,0 dS/m, bem como quando foi adicionado o condicionador de solo

Uso da água salina e condicionador de solo na produtividade de beterraba e cenoura no semi-árido do Submédio São Francisco.

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Produtividade da cenoura em função da qualidade de água e condicionador de solo Sper Sal na região Semi-Árida do Nordeste brasileiro.

Com o objetivo de avaliar o efeito de diferentes níveis de salinidade da água de irrigação e do condicionador de solo Sper Sal (ácido polimaléico) na produtividade de cenoura (Daucus caro~a L.), cultivar Brasília conduziu-se um experimento na Embrapa Semi-Arido em Petrolina -PE, no primeiro semestre de 1998. O delineamento experimental foi de blocos ao acaso com seis tratamentos (água com condutividade elétrica de 0,1dS/m - testemunha, 4,0 e 8,0 dS/m e água com condutividade elétrica 0, 1; 4,0 e 8,0 dS/m mais Sper Sal) e quatro repetições. Os resultados obtidos mostraram que as produtividades variaram de 33, 1 a 82,3 t/ha para os tratamentos irrigados com água salina mais Sper Sal e água do RiQ São Francisco, respectivamente. Não se verificou diferença significativa na produtividade quando do uso de água do São Francisco comparado á água com salinidade de 4,0 dS/m, bem como quanto do uso do Sper Sal como condicionador de solo

Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the corrected estimators. The numerical results show that the bias correction scheme yields nearly unbiased estimates. We also give an application to a real data set.Comment: 12 pages. Statistical Paper

A Sensorless PMDC Motor Speed Controller with a Logical Overcurrent Protection

A method to control the speed or the torque of a permanent-magnet direct current motor is presented. The rotor speed and the external torque estimation are simultaneously provided by appropriate observers. The sensorless control scheme is based on current measurement and switching states of power devices. The observer’s performances are dependent on the accurate machine parameters knowledge. Sliding mode control approach was adopted for drive control, providing the suitable switching states to the chopper power devices. Despite the predictable chattering, a convenient first order switching function was considered enough to define the sliding surface and to correspond with the desired control specifications and drive performance. The experimental implementation was supported on a single dsPIC and the controller includes a logic overcurrent protection

Small-sample corrections for score tests in Birnbaum-Saunders regressions

In this paper we deal with the issue of performing accurate small-sample inference in the Birnbaum-Saunders regression model, which can be useful for modeling lifetime or reliability data. We derive a Bartlett-type correction for the score test and numerically compare the corrected test with the usual score test, the likelihood ratio test and its Bartlett-corrected version. Our simulation results suggest that the corrected test we propose is more reliable than the other tests.Comment: To appear in the Communications in Statistics - Theory and Methods, http://www.informaworld.com/smpp/title~content=t71359723