COM-Poisson cure rate survival models and an application to a cutaneous melanoma data

In this paper, we develop a flexible cure rate survival model by assuming the number of competing causes of the event of interest to follow the Conway-Maxwell Poisson distribution. This model includes as special cases some of the well-known cure rate models discussed in the literature. Next, we discuss the maximum likelihood estimation of the parameters of this cure rate survival model. Finally, we illustrate the usefulness of this model by applying it to a real cutaneous melanoma data. (C) 2009 Elsevier B.V. All rights reserved.

Reliability Nonparametric Bayesian Estimation in Parallel Systems

Relevant results for (sub-)distribution functions related to parallel systems are discussed. The reverse hazard rate is defined using the product integral. Consequently, the restriction of absolute continuity for the involved distributions can be relaxed. The only restriction is that the sets of discontinuity points of the parallel distributions have to be disjointed. Nonparametric Bayesian estimators of all survival (sub-)distribution functions are derived. Dual to the series systems that use minimum life times as observations, the parallel systems record the maximum life times. Dirichlet multivariate processes forming a class of prior distributions are considered for the nonparametric Bayesian estimation of the component distribution functions, and the system reliability. For illustration, two striking numerical examples are presented.

Testing unit root based on partially adaptive estimation

This paper proposes unit tests based on partially adaptive estimation. The proposed tests provide an intermediate class of inference procedures that are more efficient than the traditional OLS-based methods and simpler than unit root tests based on fully adptive estimation using nonparametric methods. The limiting distribution of the proposed test is a combination of standard normal and the traditional Dickey-Fuller (DF) distribution, including the traditional ADF test as a special case when using Gaussian density. Taking into a account the well documented characteristic of heavy-tail behavior in economic and financial data, we consider unit root tests coupled with a class of partially adaptive M-estimators based on the student-t distributions, wich includes te normal distribution as a limiting case. Monte Carlo Experiments indicate that, in the presence of heavy tail distributions or innovations that are contaminated by outliers, the proposed test is more powerful than the traditional ADF test. We apply the proposed test to several macroeconomic time series that have heavy-tailed distributions. The unit root hypothesis is rejected in U.S. real GNP, supporting the literature of transitory shocks in output. However, evidence against unit roots is not found in real exchange rate and nominal interest rate even haevy-tail is taken into a account.

Semiparametric estimation and inference using doubly robust moment conditions

We study semiparametric two-step estimators which have the same structure as parametric doubly robust estimators in their second step. The key difference is that we do not impose any parametric restriction on the nuisance functions that are estimated in a first stage, but retain a fully nonparametric model instead. We call these estimators semiparametric doubly robust estimators (SDREs), and show that they possess superior theoretical and practical properties compared to generic semiparametric two-step estimators. In particular, our estimators have substantially smaller first-order bias, allow for a wider range of nonparametric first-stage estimates, rate-optimal choices of smoothing parameters and data-driven estimates thereof, and their stochastic behavior can be well-approximated by classical first-order asymptotics. SDREs exist for a wide range of parameters of interest, particularly in semiparametric missing data and causal inference models. We illustrate our method with a simulation exercise.

A unit root test based on partially adaptive estimation

This paper constructs a unit root test baseei on partially adaptive estimation, which is shown to be robust against non-Gaussian innovations. We show that the limiting distribution of the t-statistic is a convex combination of standard normal and DF distribution. Convergence to the DF distribution is obtaineel when the innovations are Gaussian, implying that the traditional ADF test is a special case of the proposed testo Monte Carlo Experiments indicate that, if innovation has heavy tail distribution or are contaminated by outliers, then the proposed test is more powerful than the traditional ADF testo Nominal interest rates (different maturities) are shown to be stationary according to the robust test but not stationary according to the nonrobust ADF testo This result seems to suggest that the failure of rejecting the null of unit root in nominal interest rate may be due to the use of estimation and hypothesis testing procedures that do not consider the absence of Gaussianity in the data.Our results validate practical restrictions on the behavior of the nominal interest rate imposed by CCAPM, optimal monetary policy and option pricing models.

Levenberg-Marquardt application to two-phase nonlinear parameter estimation for finned-tube coil evaporators

A procedure for calculation of refrigerant mass flow rate is implemented in the distributed numerical model to simulate the flow in finned-tube coil dry-expansion evaporators, usually found in refrigeration and air-conditioning systems. Two-phase refrigerant flow inside the tubes is assumed to be one-dimensional, unsteady, and homogeneous. In themodel the effects of refrigerant pressure drop and the moisture condensation from the air flowing over the external surface of the tubes are considered. The results obtained are the distributions of refrigerant velocity, temperature and void fraction, tube-wall temperature, air temperature, and absolute humidity. The finite volume method is used to discretize the governing equations. Additionally, given the operation conditions and the geometric parameters, the model allows the calculation of the refrigerant mass flow rate. The value of mass flow rate is computed using the process of parameter estimation with the minimization method of Levenberg-Marquardt minimization. In order to validate the developed model, the obtained results using HFC-134a as a refrigerant are compared with available data from the literature.

Estimation of the volumetric oxygen tranfer coefficient (KLa) from the gas balance and using a neural network technique

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Filtration enrichment method for isolation of auxotrophic mutants of Trichoderma harzianum rifai

A obtenção de marcas genéticas, quer sejam para resistência a drogas, quer para auxotrofia, é uma etapa trabalhosa mas importante em pesquisa genética. Esse trabalho visou a obtenção de mutantes auxotróficos de Trichoderma harzianum utilizando-se a técnica de enriquecimento por filtração. A técnica mostrou-se superior à técnica convencional de isolamento total. Doze mutantes auxotróficos obtidos foram testados quanto a estabilidade, crescimento e resistência ao fungicida benomil. Eles apresentaram taxas de crescimento e esporulação comparáveis à linhagem parental e dois mutantes foram resistentes a benomil em uma concentração de 500µg/ml.

Hair coat characteristics and sweating rate of Braford cows in Brazil

This paper deals with the effects of hair coat characteristics on the sweating rate of Brazilian Braford cows and estimation of heritabilities and genetic correlations of these traits. Data (n=1607) on hair length, coat thickness, hair diameter, number of hairs per unit area, coat reflectance and sweating rate were recorded from heifers and cows of a commercial herd managed on range under extensive system. The data were analyzed considering the following effects on the model for hair coat traits: classes of sires and contemporary groups; linear effects of month and genotype; linear and quadratic effects of age. The effect of sire was important (P<0.05) for all hair coat traits, except for number of hairs; contemporary groups affected (P<0.05) all hair coat traits; the effect of sampling month was important (P<0.05) for hair length and reflectance; genotype affected (P<0.05) hair length, diameter and coat reflectance; the quadratic effect of age was important (P<0.05) only for coat reflectance. Two models were used to analyze the sweating rate. The first model considered the following fixed effects: classes of contemporary groups and sires; linear effect of genotype, coat thickness, hair length, hair diameter, number of hairs, coat reflectance; linear and quadratic effects of time of day, age, air temperature, partial vapour pressure and radiant heat load. The second model used for the sweating rate considered the same fixed effects for the first model, except that the hair coat characteristics were adjusted for important effects used in the models to analyze hair coat traits. All meteorological factors and contemporary groups were important (P<0.05) on variation of sweating rate in both models. The Restricted Maximum. Likelihood (REML) method was used to estimate variance and covariance components under the sire model. Results included heritability estimates in narrow (h(2)) and broad (H) sense for single-trait analyzes: hair thickness (h(2)=0.16; H-2=0.26); hair length (h(2)=0.18; H-2=0.39); number of hairs (h(2)=0.08 +/- 0.07; H-2=0.08 +/- 0.07); hair diameter (h(2)=0.12 +/- 0.07; H-2=0.12 +/- 0.07); coat reflectance (h(2)=0.30; H-2=0.42); and sweating rate (h(2)=0.10 +/- 0.07; H-2=0.10 +/- 0.07). In general, the genetic correlations between the adaptive traits were favorable as for the direction to select for adaptation in tropical environment; however, they presented high standard errors. The results of this study imply that hair coat characteristics and sweating ability are important for the adaptability to heat stress and they must be better studied and further considered for selection for genetic progress of adaptation in tropical environment. (C) 2007 Elsevier B.V All rights reserved.

Evidence for a respiratory component, similar to mammalian respiratory sinus arrhythmia, in the heart rate variability signal from the rattlesnake, Crotalus durissus terrificus

Autonomic control of heart rate variability and the central location of vagal preganglionic neurones (VPN) were examined in the rattlesnake ( Crotalus durissus terrificus), in order to determine whether respiratory sinus arrhythmia (RSA) occurred in a similar manner to that described for mammals. Resting ECG signals were recorded in undisturbed snakes using miniature datalogging devices, and the presence of oscillations in heart rate (f(H)) was assessed by power spectral analysis (PSA). This mathematical technique provides a graphical output that enables the estimation of cardiac autonomic control by measuring periodic changes in the heart beat interval. At fH above 19 min(-1) spectra were mainly characterised by low frequency components, reflecting mainly adrenergic tonus on the heart. By contrast, at f(H) below 19 min(-1) spectra typically contained high frequency components, demonstrated to be cholinergic in origin. Snakes with a f(H) > 19 min(-1) may therefore have insufficient cholinergic tonus and/or too high an adrenergic tonus acting upon the heart for respiratory sinus arrhythmia ( RSA) to develop. A parallel study monitored f(Hd) simultaneously with the intraperitoneal pressures associated with lung inflation. Snakes with a fH < 19 min(-1) exhibited a high frequency (HF) peak in the power spectrum, which correlated with ventilation rate (f(V)). Adrenergic blockade by propranolol infusion increased the variability of the ventilation cycle, and the oscillatory component of the f(H) spectrum broadened accordingly. Infusion of atropine to effect cholinergic blockade abolished this HF component, confirming a role for vagal control of the heart in matching f(H) and f(V) in the rattlesnake. A neuroanatomical study of the brainstem revealed two locations for vagal preganglionic neurones (VPN). This is consistent with the suggestion that generation of ventilatory components in the heart rate variability (HRV) signal are dependent on spatially distinct loci for cardiac VPN. Therefore, this study has demonstrated the presence of RSA in the HRV signal and a dual location for VPN in the rattlesnake. We suggest there to be a causal relationship between these two observations.

The Geometric Birnbaum-Saunders regression model with cure rate

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Real-time monitoring and kinetic parameter estimation of the affinity interaction of jArtinM and rArtinM with peroxidase glycoprotein by the electrogravimetric technique

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

An accurate estimate of machining time is very important for predicting delivery time, manufacturing costs, and also to help production process planning. Most commercial CAM software systems estimate the machining time in milling operations simply by dividing the entire tool path length by the programmed feed rate. This time estimate differs drastically from the real process time because the feed rate is not always constant due to machine and computer numerical controlled (CNC) limitations. This study presents a practical mechanistic method for milling time estimation when machining free-form geometries. The method considers a variable called machine response time (MRT) which characterizes the real CNC machine's capacity to move in high feed rates in free-form geometries. MRT is a global performance feature which can be obtained for any type of CNC machine configuration by carrying out a simple test. For validating the methodology, a workpiece was used to generate NC programs for five different types of CNC machines. A practical industrial case study was also carried out to validate the method. The results indicated that MRT, and consequently, the real machining time, depends on the CNC machine's potential: furthermore, the greater MRT, the larger the difference between predicted milling time and real milling time. The proposed method achieved an error range from 0.3% to 12% of the real machining time, whereas the CAM estimation achieved from 211% to 1244% error. The MRT-based process is also suggested as an instrument for helping in machine tool benchmarking.

Roadside vegetation: estimation and potential for carbon sequestration

The present paper reports the assessment of the vegetation occupancy rate of the roadside, through analysis of aerial photographs. Using such value the potential of these areas to be employed as carbon (C) sinks was also assessed. Moreover, for the areas suitable for afforestation, the potential for carbon sequestration was estimated considering different species of vegetation, both native (scenario 1) and exotic (formed by Pinus sp. and Eucalyptus sp. - scenario 2). The study was carried out through GIS techniques and two regions were considered. A set of equations was used to estimate the rate of occupancy over the study areas, as well as amounts of fixed C under the above scenarios. The average occupancy rate was 0.06%. The simulation showed a higher potential for C sequestration in scenario 2, being the estimated amounts of CO(2) sequestered from the atmosphere per km of roadside: 131 tons of CO(2) km(-1) of highway to native species and 655 tons of CO(2) km(-1) of highway for exotic species (over period of 10 years for both estimates). If we consider the whole road network of the São Paulo State (approximately 190 000 km) and that a considerable part of this road work is suitable to receive this kind of service, it is possible to predict the very high potential for C sequestration if managers and planners consider roadside as area for afforestation.

Anaerobic threshold estimation by statistical modelling.

Anaerobic threshold (AT) is usually estimated as a change point problem by visual analysis of the cardiorespiratory response to incremental dynamic exercise. In this study, two phase linear (TPL) models of the linear-linear and linear-quadratic type were used for the estimation of AT. The correlation coefficient between the classical and statistical approaches was 0.88, and 0.89 after outlier exclusion. The TPL models provide a simple method for estimating AT that can be easily implemented using a digital computer for the automatic pattern recognition of AT.