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MATH 265

Time Series Theory and Methods

Description
Analysis of correlated data in time, trends, seasonal patterns, periodicity, autocorrelation, spectral/frequency analysis, filtering, ARIMA models, state-space models, forecasting. Applications from various fields including economics, signal processing, finance, atmospheric science. Prerequisites: Math 261A. Notes: Alternate years.

Grading
Normal Grade Rules

Units
3