Functional Data Analysis
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
- Teacher spread
- 0.286 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
Abstract Functional data analysis (FDA) models data using functions or functional parameters. The complexity of the functions is not assumed to be known in advance, so that methods are used for approximating these with as much flexibility as the data require.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Encyclopedia of Statistics in Behavioral Science
- Topic
- Optimal Experimental Design Methods
- Field
- Decision Sciences
- Canadian institutions
- McGill University
- Funders
- —
- Keywords
- Functional data analysisFlexibility (engineering)Computer scienceFunctional principal component analysisFunctional analysisData miningAlgorithmMathematicsStatisticsBiologyMachine learning
- Has abstract in OpenAlex
- yes