Chelsey Legacy will be speaking about her SLU Fellowship (summer research project).
Title: An Interactive Program Using Sums of Rational Functions to Model Correlation Structures
Autocorrelation is the correlation between a current observation and a past observation, which is useful to analyze when studying time series data. There are already methods that exist to model autocorrelation structures. However, these structures are not able to model distinct and abnormal features, such as bumps, that occur within an autocorrelation structure. These abnormalities possibly indicate interesting features of the data set that are worth further examination. This project aims to identify the most significant bumps in a series of autocorrelation and model them using sums of rational functions. An interactive R program has been created which allows the user to see a plot of the autocorrelation of a dataset and choose bumps believed to be significant. The program then uses nonlinear regression to calculate the formula used to model the data set with the selected bumps. To illustrate this program, it has been applied to time series data such as data for Disturbance Storm Time Index values, electron flux patterns, and average daily weather temperatures for Anchorage, Alaska.