API Reference
API Reference
This is a guide to FSML's public API (Application Programming Interface).
Structure
The FSML procedures are categorised into several thematic modules:
STS: Basic statistics for describing and understanding data (e.g., mean, variance, correlation)TST: Parametric and non-parametric hypothesis tests (e.g., Mann–Whitney U , analysis of variance)LIN: Statistical procedures relying heavily on linear algebra (e.g., principal component analysis, ridge regression, linear discriminant analysis)NLP: Non-linear and algorithmic procedures (e.g., k-means clustering)DST: Statistical distributions (e.g., Student's t distribution); probability density function (PDF), cumulative distribution function (CDF), and percent point function (PPF)
While the public interfaces do not include these as prefixes, the handbook makes use of these categories to give it more structure. If you are interested in exploring the code, you will recognise these in module and procedure names.
Note
Interfaces with the prefix fsml_ are part of the public API and provided through the fsml module.
Coverage
The following procedures are currently covered and have a public interface. The links will take you directly to the documentation for the API.
| Basic Statistics (STS) |
|---|
| Mean |
| Median |
| Variance |
| Standard deviation |
| Covariance |
| Linear trend |
| Correlation (Pearson) |
| Correlation (Spearman rank) |
| Linear Procedures (LIN) |
|---|
| Principal Component Analysis |
| Empirical Orthogonal Functions |
| Linear Discriminant Analysis (2-Class) |
| Ordinary Least Squares Regression |
| Ridge Regression |
| Mahalanobis Distance |
| Non-Linear Procedures (NLP) |
|---|
| Hierarchical Clustering |
| K-Means Clustering |
| Hybrid H/K-Means Clustering |