Book reviews

Statistical Papers -     

Long memory estimation for complex-valued time series

Statistics and Computing - Long memory has been observed for time series across a multitude of fields, and the accurate estimation of such dependence, for example via the Hurst exponent, is crucial...     

Bats in urban areas of Brazil: roosts,food resources and parasites in disturbed environments

Urbanization is a widespread intense land use that generally results in biodiversity decline. Among the taxa capable to adapt to urban landscapes, bats are particularly ubiquitous. Brazil has one of the world’s largest diversity of bat species and one of the highest urbanization rates of the world. Yet, few studies have synthesized the biology of bats in urban environments, especially in Brazil. To fill this gap, we systematically reviewed the published scientific literature on the bat fauna found in urban areas of Brazil. The knowledge of urban bats is still incipient and heterogeneously spatially distributed, mostly concentrated in the southeastern region of the country. The assembled list of 84 urban species, of which nineteen are new species records for urban areas (including one new family), represents 47% of the bat richness registered in the country. Thirty-one bat species (37%) were captured exclusively inside forest fragments. Moreover, we provide information on the resources used within the urban matrix by summarizing the roosting sites for 38 bat species, as well as 31 plants consumed by at least twelve bat species. Regarding parasitological aspects, we listed eleven zoonotic parasites hosted by 27 bat species and discussed their potential to become a public health threat. Likewise, we considered the different features linked to urbanization, including impacts on immunity, body condition and susceptibility to acquiring parasites, as possible bat conservation issues. Finally, we defined an agenda for bat studies in urban areas of Brazil.     

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.