بازگشت

سری های زمانی 2

سری زمانی 2 درس اختیاری به میزان چهار واحد برای دانشجویان ارشد آمار با پیشنیاز سری های زمانی 1 می باشد

 

TIME SERIES (II),

 

Contents:

In this course we have to learn something about time series in univariate

and multivariate time series in the both time domain and frequency domain

approach.

1. Time Domain Approach

Introduction

Regression, Smoothing in Time Series

Box and Jenkins Models (ARIMA) and Nonlinear Models (ARCH, GARCH,

Bilinear, Threshold Models)

Forecasting and Estimation

Lagged Regressin and Signal Detection

State Space Models (Kalman Filtering)

2. Frequency Domain Approach

Introduction

Spectral Analysis (Power Spectrum, Cross Spectrum)

Linear Filters

Signal Extraction

State space models (Kalman Filtering)

Exam:

1) Mid Term exam (40 points),  Azar, 98

2) Final Exam (60 points)

3) Seminar (+20 points)

4) Homework (up to +10 points)

References:

1) Shumway and Stoffer (2006 or 2011, 2017), Time Series Analysis and

its Applications, Springer, New York.

Fuller, W. A. (1996), An Introduction to Time Series Analysis, John Wiley,

New York.

Anderson, T. W. (1971), The Statistical Analysis of Time Series, John Wiley,

New York.

Brillinger, D. R. (2001), Time Series: Data Analysis and Theory, SIAM,

Philadelphia.

Chatfield, C. (2003), The Analysis of Time Series: An Introduction, Chapman

and Hall, London.

Cryer, J. D., Chan, K. S. (2008), Time Series Analysis, With Applications

in R Springer, New York.

Brockwell, P. T. and Davis, R. A. (2002), Introduction to Time Series and

Forecasting, 2ed. Springer, New York.

1