Evaluation of vectorization/parallelization techniques: application to nonparametric curve estimation

The simulation of statistical models in a computer is a fundamental aspect of research in the field of nonparametric curve estimation. Methods such as the FFT (Fast Fourier Transform) or WARP (Weighted Average of Rounded Points) have been developed and analysed for computer implementation of the different techniques in this realm, with the aim of reducing the computation time as much as possible. In this work we analyse two techniques with this objective. These are the vectorization of the source code in which the different algorithms are implemented, and their distributed execution. It can be observed that the vectorization of the programs can improve the results obtained with techniques such as the FFT or WARP, or, in some cases, can prevent the use of these.     

Remaining childless in affluent economies: a comparison of France, West Germany, Italy and Spain, 1994–2001 Rester sans enfant dans des sociétés d'abondances: une comparaison de la France, l'Allemagne de l'Ouest et l'Espagne, 19994–2001

This article explores why women delay childbearing and increase their likelihood to remain childless in Spain, Italy, West Germany and France. We take a macro–micro perspective and show that national institutions influence women’s life transitions, in particular partnership and motherhood. For coupled women, we find two alternative modes out of childlessness. In countries with high direct and indirect child costs, like Spain and Italy, entering a male-breadwinner couple or occupying a stable and high-income position facilitates motherhood, while in the French context motherhood is most likely in a dual-earner partnership.      

Technology,Gender and Time: A Contribution to the Debate

Using the data collected from research carried out at two Portuguese universities, this article highlights the way university lecturers currently deal with space and time. Their professional activity is not externally subjected to a specific time geometry that defines their working day. Teaching and researching time–spaces are basically task oriented. Furthermore, university lecturers are increasingly requested to perform tasks in very short time periods in order to secure financial support. To a certain extent, this pressure upon their work is facilitated by the use of technology. However, technology also causes a profound reconfiguration of working times and spaces, especially because it allows lecturers to work at any time from anywhere. This not only renders university physical spaces and times virtual, but it also leads to the colonization of several other time–spaces of their social lives. This article analyses the ambivalence and difficulty of managing time–spaces, as described by the lecturers themselves, with the objective of providing a more accurate awareness of the implications of technology on their lives, as well as the hazards of the progressive externalization of academic work, particularly for women.     

Generalized Mixtures of Gamma and Exponentials and Reliability Properties of the Maximum from Friday and Patil Bivariate Exponential Model

The minimum and maximum order statistics from many of the common bivariate exponential distributions are predominantly generalized mixtures of exponentials; however, the maximum from the Friday and Patil bivariate exponential (FPBVE) model is either a generalized mixture of three or fewer exponentials or a generalized mixture of gamma and exponentials. In this article, we obtain conditions based on the weights and parameters of the generalized mixtures of gamma and one or two exponential distributions that yield legitimate probability models. Furthermore, we analyze properties of the failure rate of the maximum from the FPBVE model. This answers a question raised in Baggs and Nagaraja (1996 Baggs , G. E. , Nagaraja , H. N. ( 1996 ). Reliability properties of order statistics from bivariate exponential distributions . Commun. Statist. Stochastic Mod. 12 : 611 – 631 .[Taylor & Francis Online] , [Google Scholar]).     

A Robust Procedure in Nonlinear Models for Repeated Measurements

Nonlinear regression models arise when definite information is available about the form of the relationship between the response and predictor variables. Such information might involve direct knowledge of the actual form of the true model or might be represented by a set of differential equations that the model must satisfy. We develop M-procedures for estimating parameters and testing hypotheses of interest about these parameters in nonlinear regression models for repeated measurement data. Under regularity conditions, the asymptotic properties of the M-procedures are presented, including the uniform linearity, normality and consistency. The computation of the M-estimators of the model parameters is performed with iterative procedures, similar to Newton–Raphson and Fisher's scoring methods. The methodology is illustrated by using a multivariate logistic regression model with real data, along with a simulation study.     

The 3 F 2 with Complex Parameters as Generating Function of Discrete Distribution

A new discrete family of probability distributions that are generated by the ₃ F ₂ function with complex parameters is presented. Some of the properties of this new family are studied as well as methods of estimation for its parameters. It affords considerable flexibility of shape which turns the distribution into an appropriate candidate for modeling data that cannot be adequately fitted by classical families with fewer parameters. Finally, three examples in the fields of Agriculture and Education are included in order to show the versatility and utility of this distribution.     

Stochastic Aging Classes for the Maximum Statistic from Friday and Patil Bivariate Exponential Distribution Family

Friday and Patil bivariate exponential (FPBVE) distribution family is one of the most flexible bivariate exponential distributions in the literature; among others, it contains the bivariate exponential models due to Freund, Marshall–Olkin, Block–Basu, and Proschan–Sullo as particular cases. In this article, we discuss the stochastic aging of the maximum statistic from FPBVE model in according to the log-concavity of its density function, i.e., in the increasing or decreasing likelihood ratio classes (ILR or DLR), and consequently in the IFR and DFR classes. Furthermore, a kind of DFR distributions which are not DLR is derived from our classification.