Package: LPStimeSeries
Version: 1.0-5
Date: 2015-03-27
Title: Learned Pattern Similarity and Representation for Time Series
Author: Learned Pattern Similarity (LPS) for time series by Mustafa Gokce Baydogan
Depends: R (>= 2.5.0)
Imports: RColorBrewer
Maintainer: Mustafa Gokce Baydogan <baydoganmustafa@gmail.com>
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. 
License: GPL (>= 2)
URL: http://www.mustafabaydogan.com/learned-pattern-similarity-lps.html
Packaged: 2015-03-27 16:33:53 UTC; baydogan
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2015-03-27 18:54:54
Built: R 4.0.2; x86_64-apple-darwin17.0; 2020-07-15 15:49:02 UTC; unix
Archs: LPStimeSeries.so.dSYM
