autoregression

This is a package for generating autoregressive models for sequential or timeseries data.

NewModelOLS(data []float64, order int) (*ARModel, error)

This function attempts to generate an autoregressive model using the method of Ordinary Least Squares. It requires some past data, as a float64 slice, and an order (or lag). If successful, a model will be returned, which can then be used to make predictions.

ARModel.Order() int

This method returns the order of the model.

ARModel.StandardError() float64

This method returns the standard error of the model. This is a measure of how far the model deviates from the data it was trained on.

ARModel.Predict(newData []float64) (float64, error)

This method returns a prediction of the next value following a given it's preceding data of length order.