Speaker
Description
Statistical analysis on temporal, spatial, graph, and probabilistic data is error-prone when the data types lack intrinsic structure. Outputs from models typically return these composite data types separately, requiring the user to assemble and apply the results correctly. This reduces the accessibility of statistics and results in error-prone analysis. Representing these data types using composite vector types makes statistical operations and data analysis easier.
In this talk, I will introduce the application of vectorised statistical operations across common dimensions not otherwise handled in traditional data structures. The vectors of vectors data type implemented in the vecvec R package is foundational for creating efficient mixed data types. The distributional and mixtime R packages leverage vecvec in order to create vectors that mix different distributions and temporal granularities together. Storing distributions with different shapes and parameterisations together in the same vector abstracts away the data handling complexity while providing a user-friendly interface for calculating distributional statistics such as the mean, quantiles, and densities. Similarly, storing time at different granularities allows combining data from different sources and facilitates forecasts across multiple levels of temporal aggregation.
These semantic vectors combine naturally in tidy rectangular data to facilitate statistically sensible multi-dimensional analysis. For instance, pairing temporal and distributional vectors yields a dataset ready for probabilistic time series forecasting, or pairing temporal and spatial vectors a dataset ready for spatio-temporal analysis.
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| Keywords: Please list up to 5 keywords to help us find the right session for your contribution. | vectors, tidy data, semantics, object-oriented programming, statistical computing |
|---|---|
| Virtual Option | This submission is for onsite presentation only |
| Video Recording | Video sharing is fine |
| The author(s) agree(s) to take responsibility and be accountable for the contents of the submission and is/are authorized to present it. | Confirm |
| Interested in serving as reviewer? | mitch.ohara-wild@monash.edu |