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Data integration via analysis of subspaces (DIVAS)
Modern data collection in many data paradigms, including bioinformatics, often incorporates multiple traits derived from different data types (i.e.,...
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Inference with non-probability samples and survey data integration: a science map** study
In recent years, survey data integration and inference based on non-probability samples have gained considerable attention. Because large...
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Data Integration and Analysis
This chapter provides a wide variety of examples of the ways in which data can be manipulated using an item-based approach, demonstrating how to...
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Augmenting business statistics information by combining traditional data with textual data: a composite indicator approach
Combining traditional and digital trace data is an emerging trend in statistics. In this respect, new data sources represent the basis for...
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Statistical data integration in survey sampling: a review
Finite population inference is a central goal in survey sampling. Probability sampling is the main statistical approach to finite population...
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Target-aware Bayesian inference via generalized thermodynamic integration
In Bayesian inference, we are usually interested in the numerical approximation of integrals that are posterior expectations or marginal likelihoods...
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Numerical Integration
Integration is a very common requirement in quantitative finance. In some cases integrals can be evaluated analytically, or at least in terms of...
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Integrating rather than collecting: statistical matching in the data flood era
Statistical matching is progressively emerging as a straightforward approach to data integration. This method of increasing importance and interest...
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Statistical integration of allele frequencies from several organizations
Genetic evidence, especially evidence based on short tandem repeats, is of paramount importance for human identification in forensic inferences. In...
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Data Preprocessing
This chapter provides a comprehensive overview of data preprocessing techniques and tools in the context of web and social media analytics. As data...
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Innovation for improving climate-related data—Lessons learned from setting up a data hub
In this article, we present a framework to assess the challenges in the climate-related data landscape. From our perspective, we describe challenges...
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Integrating probability and big non-probability samples data to produce Official Statistics
This paper introduces the pseudo-calibration estimators, a novel method that integrates a non-probability sample of big size with a probability...
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Supervised Classification of High-Dimensional Correlated Data: Application to Genomic Data
This work addresses the problem of supervised classification for high-dimensional and highly correlated data using correlation blocks and supervised...
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A flexible time-varying coefficient rate model for panel count data
Panel count regression is often required in recurrent event studies, where the interest is to model the event rate. Existing rate models are unable...
