APPLIED TIME SERIES ANALYSIS, FORECASTING AND CONTROL I

Name: APPLIED TIME SERIES ANALYSIS, FORECASTING AND CONTROL I
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Rating: 4.7 (143 reviews)

STAT 701

과목 설명

Theory and application of discrete time series models illustrated with forecasting problems. Principles of iterative model building. Representation of dynamic relations by difference equations. Autoregressive integrated Moving Average models. Identification, fitting, diagnostic checking of models. Seasonal model application to forecasting in business, economics, ecology, and engineering used at each stage, which the student analyzes using computer programs which have been specially written and extensively tested.

선수과목

Graduate/professional standing

충족 요건

STAT 801

학점

미보고

개설 시기

미보고

평점

3.67

-1.81% 과거 데이터 대비

수료율

100%

과거 데이터 대비 변화 없음

A 비율

55.56%

-16.37% 과거 데이터 대비

학급 규모

-11.89% 과거 데이터 대비

Cumulative Grade Distribution

강사 (2026 Summr)

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유사 과목

TOPICS IN APPLIED ECONOMETRICS

ECON 718

Applied time series methods.

ADVANCED FINANCIAL STATISTICS

STAT 801

Statistical theory and methodology for modern financial data. Topics include financial stochastic models based on time series and stochastic calculus, modern statistical inference, and statistical learning for financial data as well as their applications to financial problems.

TIME SERIES ANALYSIS

POLISCI 917

This course introduces students to time series methods and applications, including ARMA models, error corrections models and reduced form specifications. Course also discusses co-integration and fractional integration.

ECONOMIC FORECASTING

ECON 460

Introduction to econometric time series analysis, forecasting methods, and forecast evaluation. Covers theoretical, methodological, and applied topics, and much of the work will be hands-on data analysis.

INTRODUCTION TO TIME SERIES

STAT 349

Autocorrelation; stationarity and non-stationarity; heteroscedasticity; dynamic models; auto-regressive and moving average models; identification and fitting; forecasting; seasonal adjustment; applications for financial time series, social sciences and environmental studies.