Degree Type

Creative Component

Semester of Graduation

Summer 2020

Department

Statistics

First Major Professor

Farzad Sabzikar

Degree(s)

Master of Science (MS)

Major(s)

Statistics

Abstract

In this work, we demonstrate the application of ARTFIMA models on stable data derived from solar flare soft x-ray emissions. We study the solar flare data during a period of solar minimum which occurred most recently in July, August and September 2017. We use a two-state Hidden Markov Model to extract shorter stationary trajectories from the solar flare time series and classifying it into two states. In this work, we also introduce the ARTFIMA-GARCH model to model some of the trajectories. We do an end-to-end analysis, modeling and prediction of the solar flare data using both ARFIMA and ARTFIMA-GARCH models. We show through visual inspection and statistical tests that the models fit using ARTFIMA and the ARTFIMA-GARCH models describe the data better than the ARFIMA and ARFIMA-GARCH models which is the state of the art approach to model this data.

Copyright Owner

Kabala, Jinu

File Format

PDF

Embargo Period (admin only)

7-17-2020

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