Lycoming College Thomas Osborne Co Published physics paper titled "Using missing ordinal patterns to detect nonlinearity in time series data"

2017 Sep 14

The paper presents a new method for analyzing data see if that system generating the data obeys a set of rules that are either simple (linear) or complicated (nonlinear). The ability to identify the types of rules obeyed by a system is very important for developing mathematical models of the system. The work presented in the paper has applications in any field where data is analyzed such as astrophysics, finance, neuroscience, and climate science, just to name a few.