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Autoregressivemoving-average model
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1	Forecasting Daily and High-frequency Data M´elard, Guy Abstract Examples of high-frequency time series arise in many fields of applications, like daily sales in stores, energy consumptions by hours in office buildings, Add to Reading List Source URL: homepages.ulb.ac.be Language: English - Date: 2014-08-14 11:08:56 Statistics Time series analysis Time series models Signal processing Noise Covariance and correlation Autoregressive integrated moving average Autoregressivemoving-average model Autocorrelation Autoregressive model Time series Forecasting
2	ABOUT MANUSCRIPTS FOR IJ ITA Add to Reading List Source URL: foibg.com Language: English - Date: 2015-02-02 08:47:13 Statistics Time series models Noise Time series analysis Probability theory Regression analysis Signal processing Autoregressive integrated moving average Autoregressivemoving-average model Recurrence relation Linear regression Autoregressive model
3	Microsoft Word - slides.docx Add to Reading List Source URL: web.uvic.ca Language: English - Date: 2014-07-04 18:43:12 Time series analysis Statistics Econometrics Formal sciences Noise Economic model Cointegration Granger causality Autoregressive conditional heteroskedasticity Autoregressivemoving-average model Maximum likelihood estimation Scientific modelling
4	JOURNALOF Econometrics ELSEMER Journal Add to Reading List Source URL: econ.ucsb.edu Language: English - Date: 2011-06-16 18:31:52 Estimation theory Statistical inference Formal sciences Time series analysis Econometrics Estimator Statistics Autoregressivemoving-average model Adaptive estimator Regression analysis
5	Utilizing Predictors for Efficient Thermal Management in Multiprocessor SoCs Ayse Kivilcim Coskun† Tajana Simunic Rosing† Kenny C. Gross‡ Add to Reading List Source URL: seelab.ucsd.edu Language: English - Date: 2012-06-04 16:50:20 Physics Prediction Time series analysis State functions Continuum mechanics Heat transfer Physical quantities Temperature Branch predictor Autoregressivemoving-average model Thermodynamic temperature Forecasting
6	Introduction to Time Series Analysis. Lecture 14. Last lecture: Maximum likelihood estimation 1. Review: Maximum likelihood estimation 2. Model selection 3. Integrated ARMA models 4. Seasonal ARMA Add to Reading List Source URL: www.stat.berkeley.edu Language: English - Date: 2010-10-19 01:08:40 Estimation theory M-estimators Maximum likelihood estimation Statistical theory Autoregressivemoving-average model Akaike information criterion Likelihood function
7	Introduction to Time Series Analysis. Lecture 6. Peter Bartlett www.stat.berkeley.edu/∼bartlett/courses/153-fall2010 Last lecture: 1. Causality Add to Reading List Source URL: www.stat.berkeley.edu Language: English - Date: 2010-09-14 17:35:35 Noise Time series models Time series analysis Autoregressivemoving-average model Autoregressive model Moving-average model