Quantiles for Counts

This paper studies the estimation of conditional quantiles of counts. Given the discreteness of the data, some smoothness has to be artificially imposed on the problem. The methods currently available to estimate quantiles of count data either assume that the counts result from the discretization of a continuous process, or are based on a smoothed objective function. However, these methods have several drawbacks. We show that it is possible to smooth the data in a way that allows inference to be performed using standard quantile regression techniques. The performance and implementation of the estimator are illustrated by simulations and an application.Asymmetric maximum likelihood, Jittering, Maximum score estimator, Quantile regression, Smoothing.

Quantiles for Fractions and Other Mixed Data

This paper studies the estimation of quantile regression for fractional data, focusing on the case where there are mass-points at zero or/and one. More generally, we propose a simple strategy for the estimation of the conditional quantiles of data from mixed distributions, which combines standard results on the estimation of censored and Box-Cox quantile regressions. The implementation of the proposed method is illustrated using a well-known dataset.

Picture-based task definition and parameterization support system

Applications for task definition and automation are valuable tools to automated software engineering area. This paper describes a solution to support a parameterized task definition using screen capture images. The approach allows the capture of a sequence of actions defined by the user. Through the captured sequence of actions, the approach assists in the implementation of task automation processes. Based on picture-driven computing the proposed tool aims to reduce the challenges that users face while trying to define tasks. This approach provides also a foundation for the creation of picture-driven based tests for interactive systems, enabling to test any interactive system but also allowing for the definition, parameterization and execution of tests that might involve the use of several independent interactive systems.info:eu-repo/semantics/acceptedVersio

Satisfaction regarding the methods used to evaluate hotel performance

This study has four specific objectives: to analyse the association between hotel features and the methods used to evaluate hotel performance; to analyse the convergence between what the theory considers as appropriate performance evaluation methods, and the opinion of the hotels’ financial managers; to identify the factors that explain why the same method is considered appropriate in some hotels and not in others; to analyse whether there is an association between the method used to evaluate hotel performance and customer satisfaction. Data collection was made using two sequential methods. Firstly, we conducted a survey directed at the financial managers of 3, 4 and 5-star hotels located in Portugal, where we obtained 189 completed surveys. Secondly, we collected information regarding the degree of customer satisfaction for the hotels responding to the initial survey using the information available on the online platform Tripadvisor.com. The results obtained allow us to indicate as main contributions the following: validation of the expectations confirmation paradigm as an adequate theoretical model to explain customer satisfaction in hotels, namely showing that the performance evaluation methods can be regarded as factors affecting the actual customer experience; to demonstrate that the satisfaction indicator room is what contributes the most to the level of overall customer satisfaction; to demonstrate the existing convergence between what the theory considers as appropriate performance evaluation methods, and the opinion of the hotels’ financial managers, unlike what was previously reported in other industries.info:eu-repo/semantics/publishedVersio

Quantiles for Fractions and Other Mixed Data

This paper studies the estimation of quantile regression for fractional data, focusing on the case where there are mass-points at zero or/and one. More generally, we propose a simple strategy for the estimation of the conditional quantiles of data from mixed distributions, which combines standard results on the estimation of censored and Box-Cox quantile regressions. The implementation of the proposed method is illustrated using a well-known dataset

A public health approach to patient-centredness in embryo research

Looking at patient-centredness through the lens of public health is needed for responsible governance of human embryo research. This study aimed to explore patients’ experiences and perspectives on information about and consent for research with human embryos, to sustain the development of policies and guidelines.info:eu-repo/semantics/publishedVersio

Quantiles for counts

This paper studies the estimation of conditional quantiles of counts. Given the discreteness of the data, some smoothness has to be artificially imposed on the problem. The methods currently available to estimate quantiles of count data either assume that the counts result from the discretization of a continuous process, or are based on a smoothed objective function. However, these methods have several drawbacks. We show that it is possible to smooth the data in a way that allows inference to be performed using standard quantile regression techniques. The performance and implementation of the estimator are illustrated by simulations and an application.