Ricerc@Sapienza

We propose a capture–recapture model for estimating the size of a population based on multiple lists in presence of out-of-scope units (false captures). Our Bayesian approach makes use of a class of log–linear models with a latent structure. We also address the presence of sources providing partial information implementing a Gibbs Sampler algorithm which generates a sample from the posterior distribution of the population size in the presence of missing data. The proposed method is applied to simulated data sets.

We propose a capture–recapture model for estimating the size of a population of interest based on a set of administrative sources and/or surveys in the presence of out-of-scope units (false captures). Our Bayesian approach makes use of a certain class of log - linear models with a latent structure. We also address the presence of sources providing partial information implementing a Gibbs Sampler algorithm which generates from the posterior distribution of the population size in presence of missing data. The proposed method is applied to simulated data sets

We consider the problem of estimating the size of a population of interest, or ``target population'', by integrating multiple data sources. Each source provides a list of the units of our population.

Anthropogenic hybridization is recognized as a major and increasing threat to biodiversity. The estimation of prevalence of hybrids (proportion of hybrids in the total population) is of paramount importance to understand the extent of the phenomenon and consequently inform appropriate management policies.

Although knowledge of reproductive parameters is critical to project the chances of persistence of small populations, no data on basic reproductive traits have ever been estimated for the relict Apennine brown bear population (central Italy). From 2005-2014, as part of an ongoing ecological investigation, we compiled re-sight data on marked adult female bears (3 ? n ?