Learned Pattern Similarity and Representation for Time Series
Description
Learned Pattern Similarity (LPS) for time series.
Implements a novel approach to model the dependency structure
in time series that generalizes the concept of autoregression to local
auto-patterns. Generates a pattern-based representation of time series
along with a similarity measure called Learned Pattern Similarity (LPS).
Introduces a generalized autoregressive kernel.This package is based on the
'randomForest' package by Andy Liaw.