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Regression Analysis of Time Series
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#	Item
201	AN EMPIRICAL STUDY OF THE DYNAMICS OF SYDNEY SUBURBAN RAIL PATRONAGE AND ITS IMPLICATIONS FOR BEFORE AND AFTER STUDIES Gallagher Add to Reading List Source URL: www.atrf.info Language: English - Date: 2011-12-20 20:33:18 Statistical tests Regression analysis Parametric statistics Distributed lag Durbin–Watson statistic Autoregressive conditional heteroskedasticity Autocorrelation F-test Dummy variable Statistics Time series analysis Econometrics
202	HYDROL4117 Journal of Hydrology[removed]±000 www.elsevier.com/locate/jhydrol Add to Reading List Source URL: cawcr.gov.au Language: English - Date: 2009-12-02 21:49:43 Weather prediction Time series analysis Error Regression analysis Measurement Quantitative precipitation forecast Rain Forecast error Forecasting Statistics Atmospheric sciences Meteorology
203	Gridding of Design Rainfall Parameters for the IFD Revision Project for Australia Cynthia The Hydrologist, Climate and Water Division, Bureau of Meteorology, Sydney, Australia E-mail: [removed] Add to Reading List Source URL: www.bom.gov.au Language: English - Date: 2013-06-17 20:31:09 Interpolation Data analysis Time series analysis Smoothing spline Thin plate spline Smoothing Multivariate interpolation Data transformation USGS DEM Statistics Splines Regression analysis
204	Short Term Traffic Flow Prediction Edward Chung, Natalia Rosalion INTRODUCTION In recent years the traditional objective of improving road network efficiency is being supplemented by greater emphasis on safety, incident Add to Reading List Source URL: www.atrf.info Language: English - Date: 2011-12-06 18:16:53 Autoregressive integrated moving average Box–Jenkins Forecasting Regression analysis Traffic flow Linear regression Time series Autoregressive conditional heteroskedasticity Autoregressive–moving-average model Statistics Time series analysis Econometrics
205	Performance of the FSU Hurricane Superensemble during 2005 Atlatic Season Add to Reading List Source URL: www.ofcm.gov Language: English - Date: 2009-08-03 13:45:40 Econometrics Statistical forecasting Time series analysis Tropical cyclone forecast model Estimation theory Forecasting National Hurricane Center Linear regression Met Office Statistics Meteorology Atmospheric sciences
206	HYDROL4117 Journal of Hydrology[removed]±000 www.elsevier.com/locate/jhydrol Add to Reading List Source URL: www.cawcr.gov.au Language: English - Date: 2009-12-02 21:49:43 Weather prediction Time series analysis Error Regression analysis Measurement Quantitative precipitation forecast Rain Forecast error Forecasting Statistics Atmospheric sciences Meteorology
207	VAR Forecasting Models of the Australian Economy: A Preliminary Analysis Add to Reading List Source URL: www.rba.gov.au Language: English - Date: 2012-11-19 01:25:43 Vector autoregression Bayesian VAR Economic model Trend estimation Forecasting Unit root Macroeconomic model Regression analysis Time series Statistics Time series analysis Econometrics
208	Regional Environmental Change manuscript No. (will be inserted by the editor) Testing instrumental and downscaled reanalysis time series for temperature trends in NE of Spain in the last century. M. Turco, R. Marcos, P. Add to Reading List Source URL: pere.quintanasegui.com Language: English - Date: 2012-11-13 05:10:23 Parametric statistics Actuarial science Stepwise regression Linear regression Homogeneity Intelligence quotient Statistical power Statistics Regression analysis Econometrics
209	FOLLOW-UP NOTE ON MARKET STATE MODELS In an earlier note I outlined some of the available techniques used for modeling market states. The following is an illustration of how these techniques can be applied in practice. Add to Reading List Source URL: www.jonathankinlay.com Language: English - Date: 2013-08-16 18:52:04 Time series analysis Markov models Econometrics Markov chain Autoregressive conditional heteroskedasticity Errors and residuals in statistics Estimation theory Coefficient of determination Normal distribution Statistics Regression analysis Least squares
210	Chapter 26 Time Series So far, we have assumed that all data points are pretty much independent of each other. In the chapters on regression, we assumed that each Yi was independent of every other, given its Xi , and we Add to Reading List Source URL: www.stat.cmu.edu Language: English - Date: 2012-05-02 00:40:49 Time series analysis Stochastic processes Ergodic theory Stationary process Autocorrelation Time series Autocovariance Ergodic process Covariance Statistics Covariance and correlation Signal processing

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