Physical Sciences and Mathematics Commons^™

Feasibility Of Multi-Year Forecast For The Colorado River Water Supply: Time Series Modeling, Brian Plucinski

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

The Colorado River is one of the largest resources for water in the United States, as well as being an important asset to the economy. Previous studies have shown a connection between the Great Salt Lake and the Colorado River. This study used time series analysis to build models to predict the water supply of the Colorado River ten years out. These models used data from the Colorado River in addition to Great Salt Lake water elevation. Several models suggest a decline in water supply from 2013 – 2020, before starting to increase. These predictions differ from predictions published by …

Regime Switching In Cointegrated Time Series, Bradley David Zynda Ii

Undergraduate Honors Capstone Projects

Volatile commodities and markets can often be difficult to model and forecast given significant breaks in trends through time. To account such breaks, regime switching methods allow for models to accommodate abrupt changes in behavior of the data. However, the difficulty often arises in beginning the process of choosing a model and its associated parameters with which to represent the data and the objects of interest. To improve model selection for these volatile markets, this research examines time series with regime switching components and argues that a synthesis of vector error correction models with regime switching models with ameliorate financial …

Visual Data Mining Techniques For Functional Actigraphy Data: An Object-Oriented Approach In R, Abbass Sharif

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Actigraphy, a technology for measuring a subject's overall activity level almost continuously over time, has gained a lot of momentum over the last few years. An actigraph, a watch-like device that can be attached to the wrist or ankle of a subject, uses an accelerometer to measure human movement every minute or even every 15 seconds. Actigraphy data is often treated as functional data. In this dissertation, we discuss what has been done regarding the visualization of actigraphy data, and then we will explain the three main goals we achieved: (i) develop new multivariate visualization techniques for actigraphy data; (ii) …

A Comparison Of Prediction Methods Of Functional Autoregressive Time Series, Devin Didericksen

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Functional data analysis (FDA) is a relatively new branch of statistics that has seen a lot of expansion recently. With the advent of computer processing power and more efficient software packages we have entered the beginning stages of applying FDA methodology and techniques to data. Part of this undertaking should include an empirical assessment of the effectiveness of some of the tools of FDA, which are sound on theoretical grounds. In a small way, this project helps advance this objective.

This work begins by introducing FDA, scalar prediction techniques, and the functional autoregressive model of order one - FAR(1). Two …

Detection Of Changes In Financial Time Series, Rich Madsen

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

The purpose of this paper is to examine and model data from several years of foreign currency trading, to determine if one or more change points has occured in the data, and to estimate when those change points took place. Leading up to the analysis of the data we will construct and develop several statistics which we will use to determine if a change point has occured.

This paper falls into the area of computational statistics and will make use of Splus and the S+GARCH module within Splus. Heavy use will also be made of C++. The models that we …