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Recently, several statistical models or programs have been developed to predict outcomes for early breast cancer patients [ 5- 10].
The generic statistical model was programmed in R (version 2.14.1; R Development Core Team, Vienna, Austria) to project pneumococcal disease outcomes from birth to death for a hypothetical Chinese birth cohort of 16 million infants.
These could also arise due to differing adjustments in the statistical models, different screening programs or ways of diagnosing BCIS, or by chance.
Such disclosure should include all raw data that is, data as originally collected in accordance with research protocols, the research protocols themselves, and all methods (including computer programs used for statistical modeling).
The goal of this analysis was to describe how a typical laboratory (a statistical modeling construct) participating in the IQA Program performed over time.
Instead, probabilistic programming is a tool for statistical modeling.
Based on this statistical modeling, we propose to use a chance-constrained programming approach to design a distributed beamforming algorithm.
Statistical Modeling.
Statistical Modeling of RNA-Seq Data.
Statistical modeling, shape representation.
Statistical modeling benefits from visual exploration.
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