HOME > 상세정보

상세정보

Introduction to time series using Stata / Rev. ed

Introduction to time series using Stata / Rev. ed (2회 대출)

자료유형
단행본
개인저자
Becketti, Sean.
서명 / 저자사항
Introduction to time series using Stata / Sean Becketti.
판사항
Rev. ed.
발행사항
College Station, Tex. :   Stata Press,   c2020.  
형태사항
xxv, 446 p. : ill. ; 24 cm.
ISBN
9781597183062 (pbk.) 1597183067 (pbk.)
서지주기
Includes bibliographical references and index.
일반주제명
Mathematical statistics --Data processing.
000 00000nam u2200205 a 4500
001 000046025720
005 20200423163648
008 200423s2020 txua b 001 0 eng
020 ▼a 9781597183062 (pbk.)
020 ▼a 1597183067 (pbk.)
040 ▼a 211009 ▼c 211009 ▼d 211009
082 0 4 ▼a 519.50285 ▼2 23
084 ▼a 519.50285 ▼2 DDCK
090 ▼a 519.50285 ▼b B396i1
100 1 ▼a Becketti, Sean.
245 1 0 ▼a Introduction to time series using Stata / ▼c Sean Becketti.
250 ▼a Rev. ed.
260 ▼a College Station, Tex. : ▼b Stata Press, ▼c c2020.
300 ▼a xxv, 446 p. : ▼b ill. ; ▼c 24 cm.
504 ▼a Includes bibliographical references and index.
650 0 ▼a Mathematical statistics ▼x Data processing.
945 ▼a KLPA

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 과학도서관/Sci-Info(2층서고)/ 청구기호 519.50285 B396i1 등록번호 121253007 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

목차

Just enough Stata
Getting started
All about data
Looking at data
Statistics
Odds and ends
Making a date
Typing dates and date variables
Looking ahead





Just enough statistics
Random variables and their moments
Hypothesis tests
Linear regression
Multiple-equation models
Time series





Filtering time-series data
Preparing to analyze a time series
The four components of a time series
Some simple filters
Additional filters
Points to remember





A first pass at forecasting
Forecast fundamentals
Filters that forecast
Points to remember
Looking ahead





Autocorrelated disturbances
Autocorrelation
Regression models with autocorrelated disturbances
Testing for autocorrelation
Estimation with first-order autocorrelated data
Estimating the mortgage rate equation
Points to remember





Univariate time-series models
The general linear process
Lag polynomials: Notation or prestidigitations?
The ARMA model
Stationarity and invertibility
What can ARMA models do?
Points to remember
Looking ahead





Modeling a real-world time series
Getting ready to model a time series
The Box-Jenkins approach
Specifying an ARMA model
Estimation
Looking for trouble: Model diagnostic checking
Forecasting with ARIMA models
Comparing forecasts
Points to remember
What have we learned so far?
Looking ahead





Time-varying volatility
Examples of time-varying volatility
ARCH: A model of time-varying volatility
Extensions to the ARCH model
Points to remember





Model of multiple time series
Vector autoregressions
A VAR of the U.S. macroeconomy
Who''s on first?
SVARs
Points to remember
Looking ahead





Models of nonstationary times series
Trend and unit roots
Testing for unit roots
Cointegration: Looking for a long-term relationship
Cointegrating relationships and VECM
From intuition to VECM: An example
Points to remember
Looking ahead





Closing observations
Making sense of it all
What did we miss?
Farewell





References

관련분야 신착자료

Bertsimas, Dimitris (2022)