From 7607943c633e590c05683a87d6e81467a77169a0 Mon Sep 17 00:00:00 2001 From: PetoLau Date: Thu, 8 Mar 2018 22:26:28 +0100 Subject: [PATCH] #4 Update: changed one sentence --- paper/paper.md | 4 ++-- paper/paper.pdf | Bin 157009 -> 156767 bytes 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/paper/paper.md b/paper/paper.md index 7d2c289..7c0c450 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -11,7 +11,7 @@ affiliations: - name: Faculty of Informatics and Information Technologies, Slovak University of Technology in Bratislava index: 1 -date: 7 March 2018 +date: 8 March 2018 bibliography: paper.bib output: pdf_document --- @@ -34,6 +34,6 @@ Figure 1. The comparison of model-based time series representations on electrici Additional useful functions and methods related to time series representations were also implemented. The `TSrepr` package includes functions for normalisations and denormalisations of time series - z-score and min-max methods. It supports the simple computation of the windowing method, a matrix of representations and forecasting accuracy measures (MAE, RMSE, MAPE, sMAPE etc.). Methods (functions) were implemented in base R and also in C++ for fast computations. In R, C++ programmes can be written thanks to the package Rcpp [@rcpp]. -The general package for time series representations computations had missed so far. The CRAN's time series task view proves the previous statement. Packages `TSMining` [@tsmining] and `jmotif` [@jmotif] both includes implementations of PAA and SAX time series representations methods. However, these packages are mainly focused on motif discovery in time series. +So far, no general package for time series representations computations has been created. The CRAN's time series task view proves the previous statement. Packages `TSMining` [@tsmining] and `jmotif` [@jmotif] both includes implementations of PAA and SAX time series representations methods. 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