6533b861fe1ef96bd12c5621

RESEARCH PRODUCT

Bayesian Hierarchical Models for Random Routes in Finite Populations

Begoña FontMaria J. Bayarri

subject

education.field_of_studyComputer sciencePosterior probabilityPopulationBayesian probabilitySampling (statistics)Conditional probability distributioncomputer.software_genresymbols.namesakesymbolsData miningeducationcomputerSelection (genetic algorithm)RandomnessGibbs sampling

description

In many practical situations involving sampling from finite populations, it is not possible (or it is prohibitely expensive) to access, or to even produce, a listing of all of the units in the population. In these situations, inferences can not be based on random samples from the population. Random routes are widely used procedures to collect data in absence of well defined sampling frames, and they usually have either been improperly analyzed as random samples, or entirely ignored as useless. We present here a Bayesian analysis of random routes that incorporates the information provided but carefully takes into account the non- randomness in the selection of the units.

https://doi.org/10.1007/978-3-642-80098-6_25