This code solves a regression problem. Two methods are implemented:
- for linear regression (KQS)
- for quadratic functions, transformed as a linear problem It returns the m, t (or quadratic: a, lambda) parameter and the residuals (y - y_hat).
- datapoints = build object where a datapoint consist of a week and product price
- DataPoint = a simple datapoint with week and price
- DatePointOverview = a abstract class to have datapoints relating to each other via DataPoint class and x and y array seperated (for calculating reasons)
- mathfunctions = interface, which contracts the functions to implement (for global usage)
- Regression = the interface to contract classes which want to interact
- regression = two methods implemented in Java
- LinearModel = implementation of the linear problem (KQS)
- QuadraticFunction = implementation of the quadratic problem, with log transformation and then processed like a linear problem