Patterns in static

Apophenia

An outline of the library

The narrative in this section goes into greater detail on how to use the components of Apophenia. You are encouraged to read A quick overview first.

This overview begins with the apop_data set, which is the central data structure used throughout the system. Section Databases covers the use of the database interface, because there are a lot of things that a database will do better than a matrix structure like the apop_data struct.

Section Models covers statistical models, in the form of the apop_model structure. This part of the system is built upon the apop_data set to hold parameters, statistics, data sets, and so on.

Histosec covers probability mass functions, which are statistical models built directly around a data set, where the chance of drawing a given observation is proportional to how often that observation appears in the source data. There are many situations where one would want to treat a data set as a probability distribution, such as using apop_kl_divergence to find the information loss from an observed data set to a theoretical model fit to that data.

Section Tests & diagnostics covers traditional hypothesis testing, beginning with common statistics that take an apop_data set or two as input, and continuing on to generalized hypothesis testing for any apop_model.

Because estimation in the apop_model relies heavily on maximum likelihood estimation, Apophenia's optimizer subsystem is extensive. Optimization offers some additional notes on optimization and how it can be used in non-statistical contexts.

Data sets

Databases

Models

Histosec

Tests & diagnostics

Optimization

Assorted