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Nov 23, 2024
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2020-2021 Catalog [ARCHIVED PUBLICATION] Use the dropdown above to select the current catalog.
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MATH155 HM - Time Series
Credit(s): 3
Instructor(s): Williams
Offered: Spring, alternate years
Description: An introduction to the theory of statistical time series. Topics include decomposition of time series, seasonal models, forecasting models including causal models, trend models, and smoothing models, autoregressive (AR), moving average (MA), and integrated (ARIMA) forecasting models. Time permitting, we will also discuss state space models, which include Markov processes and hidden Markov processes, and derive the famous Kalman filter, which is a recursive algorithm to compute predictions. Statistical software will be used as a tool to aid calculations required for many of the techniques.
Prerequisite(s): Permission of instructor
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