Book reviews

Statistical Papers -     

Accurate estimation for extra-Poisson variability assuming random effect models

In this study, the components of extra-Poisson variability are estimated assuming random effect models under a Bayesian approach. A standard existing methodology to estimate extra-Poisson variability assumes a negative binomial distribution. The obtained results show that using the proposed random effect model it is possible to get more accurate estimates for the extra-Poisson variability components when compared to the use of a negative binomial distribution where it is possible to estimate only one component of extra-Poisson variability. Some illustrative examples are introduced considering real data sets.     

Smoothed bootstrap bandwidth selection for nonparametric hazard rate estimation

A smoothed bootstrap method is presented for the purpose of bandwidth selection in nonparametric hazard rate estimation for iid data. In this context, two new bootstrap bandwidth selectors are established based on the exact expression of the bootstrap version of the mean integrated squared error of some approximations of the kernel hazard rate estimator. This is very useful since Monte Carlo approximation is no longer needed for the implementation of the two bootstrap selectors. A simulation study is carried out in order to show the empirical performance of the new bootstrap bandwidths and to compare them with other existing selectors. The methods are illustrated by applying them to a diabetes data set.     

“He invited me and didn't ask anything in return” Migration and Mobility as Vulnerabilities for Sexual Exploitation among Female Adolescents in Mexico

Although human trafficking is recognized as a major human rights violation, there is limited evidence regarding the vulnerabilities that contribute to female adolescents’ risk of being forced or coerced into the sex trade. Vulnerabilities such as gender‐based violence, economic and social inequalities have been shown to shape the risk of sexual exploitation among adolescents. In‐depth interviews (n=18) with current sex workers who reported being deceived or forced into the sex trade as adolescents (<17 years old) were analysed to explore their experiences of migration and mobility in Mexico. Driven by socio‐economic and vulnerabilities in home communities, adolescents often engaged in internal migration and mobility to other Mexican communities and states. Migration and mobility further predisposed them to social isolation, economic hardship and abuse, which were used as tools to trick them into the sex trade. Policies that support safer migration for adolescents in origin, transit, and destination communities are needed.     

Classification rules for triply multivariate data with an AR(1) correlation structure on the repeated measures over time

In this article we study the problem of classification of three-level multivariate data, where multiple q$q$-variate observations are measured on u$u$-sites and over p$p$-time points, under the assumption of multivariate normality. The new classification rules with certain structured and unstructured mean vectors and covariance structures are very efficient in small sample scenario, when the number of observations is not adequate to estimate the unknown variance–covariance matrix. These classification rules successfully model the correlation structure on successive repeated measurements over time. Computation algorithms for maximum likelihood estimates of the unknown population parameters are presented. Simulation results show that the introduction of sites in the classification rules improves their performance over the existing classification rules without the sites.