Transcription of Introduction to Time Series Analysis. Lecture 1.
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Introduction to Time Series Analysis. Lecture 1.
Introduction to Time Series analysis . Lecture Bartlett1. Organizational Objectives of time Series analysis . Overview of the Time Series Time Series modelling: Chasing Issues Peter Bartlett. Office hours: Tue 11-12, Thu10-11(Evans 399). Joe Neeman. Office hours: Wed 1:30 2:30, Fri 2-3(Evans ???). bartlett/courses/153-fall2010/Check it for announcements, assignments, slides, .. Text:Time Series analysis and its Applications. With R Examples,Shumway and Stoffer. 2nd Edition. IssuesClassroom and Computer Lab Section:Friday 9 11, in 344 tomorrow, August 27:Sign up for computer accounts. Introduction to :Lab/Homework Assignments (25%): posted on the involve a mix of pen-and-paper and computer exercises. You may useany programming language you choose (R, Splus, Matlab, python).Midterm Exams (30%): scheduled for October 7 and November 9,at (10%): analysis of a data set that you Exam (35%): scheduled for Friday, December Time Series0100020003000400050006000700005010 01502002503003504004A Time Series1960196519701975198019851990050100 150200250300350400year5A Time Series1960196519701975198019851990050100 150200250300350400year$6A Time Series1960196519701975198019851990050100 150200250300350400year$SP500: 1960 19907A Time $SP500: Jan Jun 19878A Time Series2402502602702802903003100510152025 30$SP500 Jan Jun 1987.
Spectral analysis 4. State space models(?) (a) ARMAX models. (b) Forecasting, Kalman filter. (c) Parameter estimation. 28. Time Series Models A time series model specifies the joint distribution of the se-quence {Xt} of random variables. For example:
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