Course Contents
Stochastic Process, Stationary Time Series, Exponential smoothing techniques, auto-correlation and auto-covariance, estimates functions and standard error of the auto-correlation function (ACF) and PACF, Periodogram, Linear stationary models: Auto Regressive, Moving average and mixed models, Non-stationary models, general ARIMA notations and models, minimum mean square forecasting. ARIMA Seasonal models.
Course Synopsis
To familiarize the students with different time series components, smoothing and forecasting techniques and model building.
Course Learning Outcomes
Students will learn about Time Series data and its different components. They will also learn to identify the underlying stochastic model of a time series and to construct the estimated models based on available data. And hence they will get familiar with different forecasting techniques and methods.
Time Series Data|PANEL DATA|CROSS SECTION DATA by Analytics University
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Forecasting: Exponential Smoothing, MSE by Joshua Emmanuel
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Time Series Analysis - 6.3.2 - Double Exponential Smoothing by Bob Trenwith
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Three parameter smoothing (Holt-Winters Method) by Eco309spr14
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Correlations, Autocorrelations and Correlogram by Gmaz
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Introduction to Time Series Analysis: Part 1 by Scholartica Channel
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Introduction to Time Series Analysis: Part 2 by Scholartica Channel
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Basics of ARMA and ARIMA Modeling #arima #arma #boxjenkins #financialeconometrics #timeseries by CrunchEconometrix
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Time Series Analysis and Forecast - Tutorial 1 - Concept by Iman
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Time Series Analysis and Forecast - Tutorial 3 - ARMA by Iman
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Book Title : Introduction to Time Series Analysis and Forecasting
Author : Douglas C. Montgomery, Cheryl L. Jennings, Murat Kulahci
Edition : 1st
Publisher : John Wiley and sons, New York
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Book Title : The Analysis of Time Series: An Introduction
Author : Chris Chatfield
Edition : Sixth Edition
Publisher : CHAPMAN & HALL/CRC
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Title : Analysis and Forecasting of Seasonal Time Series by Dr. Akram M. Chaudhry
Type : Other
View Analysis and Forecasting of Seasonal Time Series by Dr. Akram M. Chaudhry
Title : Chapter # 19 Time Series Analysis and Forecasting by Dr. Akram M. Chaudhry
Type : Other
View Chapter # 19 Time Series Analysis and Forecasting by Dr. Akram M. Chaudhry
Title : Hyde Park purse snatchings in Chicago 28 day periods — Dataset — DataMarket
Type : Assignment
View Hyde Park purse snatchings in Chicago 28 day periods — Dataset — DataMarket
Title : Monthly milk production pounds per cow. Jan 62 – Dec 75 — Dataset — DataMarket
Type : Assignment
View Monthly milk production pounds per cow. Jan 62 – Dec 75 — Dataset — DataMarket
Title : Quarterly production of woollen yarn in Australia tonnes. Mar 1965 – Sep 1994. — Dataset — DataMarket
Type : Assignment
View Quarterly production of woollen yarn in Australia tonnes. Mar 1965 – Sep 1994. — Dataset — DataMarket
Title : Analysis of Time Series an Introduction by Chris Chatfeild (Fifth Edition))
Type : Curriculum Book
View Analysis of Time Series an Introduction by Chris Chatfeild (Fifth Edition))