منابع مشابه
Parametric Distributions of Complex Survey Data under Informative Probability Sampling
The sample distribution is defined as the distribution of the sample measurements given the selected sample. Under informative sampling, this distribution is different from the corresponding population distribution, although for several examples the two distributions are shown to be in the same family and only differ in some or all the parameters. A general approach of approximating the margina...
متن کاملScalable Approximate Bayesian Inference for Outlier Detection under Informative Sampling
Government surveys of business establishments receive a large volume of submissions where a small subset contain errors. Analysts need a fast-computing algorithm to flag this subset due to a short time window between collection and reporting. We offer a computationallyscalable optimization method based on non-parametric mixtures of hierarchical Dirichlet processes that allows discovery of multi...
متن کاملAdaptive Informative Sampling for Active Learning
Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically choose data instances that maximize disagreement among the label predictions across an ensemble of classifiers. Many classifiers with different underlying structures could fit this framework, but some ensembles are more s...
متن کاملBayesian geostatistical modeling with informative sampling locations
We consider geostatistical models that allow the locations at which data are collected to be informative about the outcomes. Diggle et al. [2009] refer to this problem as preferential sampling, though we use the term informative sampling to highlight the relationship with the longitudinal data literature on informative observation times. In the longitudinal setting, joint models of the observat...
متن کاملBayesian geostatistical modelling with informative sampling locations.
We consider geostatistical models that allow the locations at which data are collected to be informative about the outcomes. A Bayesian approach is proposed, which models the locations using a log Gaussian Cox process, while modelling the outcomes conditionally on the locations as Gaussian with a Gaussian process spatial random effect and adjustment for the location intensity process. We prove ...
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ژورنال
عنوان ژورنال: Journal of Survey Statistics and Methodology
سال: 2016
ISSN: 2325-0984,2325-0992
DOI: 10.1093/jssam/smw032