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  2. STAT 131

Introduction to Time Series & Prediction
STAT 131

Course Information

Description

Introduction to time series models and forecasting. Introduction to classical time series model: autoregressive, moving average, ARIMA models. Some concepts from stochastic processes: martingales, stationarity, Gaussian processes, Brownian motions, ergodic theorems. Some aspects of advanced time series: hidden Markov models, state space models, filtering, smoothing, Kalman filters, sequential Monte Carlo methods.

School Faculty of Arts & Sciences
Credits 4
Cross Reg

Available for Harvard Cross Registration

Department Statistics
Course Component Lecture
Subject Statistics
Grading Basis FAS Letter Graded
General Education N/A
Quantitative Reasoning with Data Yes
Divisional Distribution Science & Engineering & Applied Science
Course Level For Undergraduate and Graduate Students