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Vector Autoregression Model for Time Series Analysis using high performance linear algebra libraries

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Introduction

This project aims to offer the tools required to analyze and forecast time series using VAR models.

To generate synthetic data see GenTS.

To find the best model for a given data see SolverTS.

Dependencies

Make sure you have installed the dependencies:

  • g++ 4.7 or later
  • GNU make 3.81 or later
  • Intel MKL 2017 or later

Getting Started

Building

To build the program from the source code:

make start

Running

GenTS

./gen -var N -dep N -instances N [-ivar N -idep N] [-noise R]

SolverTS

./test [-training R] < dataFile

Authors

This repository contains the source code of GenTS and SolverTS. Both projects are at early stages and under active development. The developer of the project is Alfonso L. Castaño, advised by D. Giménez et al. as part of the project Desarrollo y estudio de algoritmos para la busqueda del mejor modelo econometrico en problemas de ciencias de la salud.

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Vector Autoregression Model for Time Series Analysis using high performance linear algebra libraries

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