Visible to Intel only — GUID: GUID-32745EC8-A4D9-457E-82BC-288EF0A353C0

Visible to Intel only — GUID: GUID-32745EC8-A4D9-457E-82BC-288EF0A353C0

## Application Notes for Intel® oneAPI Math Kernel Library Summary Statistics

Summary Statistics is a subcomponent of the Vector Statistics domain of Intel® oneAPI Math Kernel Library. Summary Statistics provides you with functions for initial statistical analysis, and offers solutions for parallel processing of multi-dimensional datasets.

These Application Notes cover the algorithms, interfaces, usage models, and the most important features of Summary Statistics.

### Algorithms and Interfaces in Summary Statistics

See Algorithms and Interfaces in Summary Statistics for information on methods and usage specifics of Summary Statistics algorithms.

### Common Usage Model of Summary Statistics

Common Usage Model of Summary Statistics gives you an idea of what a typical Summary Statistics application looks like.

### Dealing With Out-Of-Memory Datasets

If you have to deal with large datasets that do not fit into your target system’s memory, consider Processing Data in Blocks. The Computing Quantiles for Streaming Data section covers some steps that are specific to estimating quantiles for out-of-memory data.

### Working with Data that Has Outliers and Missing Values

The chapters Detecting Outliers in Datasets and Dealing with Missing Observations can help you process imperfect real-world data.

- Legal Information

- About This Document

- About Summary Statistics

- Algorithms and Interfaces in Summary Statistics

- Common Usage Model of Summary Statistics Algorithms

- Processing Data in Blocks

- Detecting Outliers in Datasets

- Dealing with Missing Observations

- Computing Quantiles for Streaming Data

- Bibliography

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