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Time series models
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111	ESTIMATING THE EXPECTED PREDICTIVE OF ECONOMETRIC MODELS Add to Reading List Source URL: fairmodel.econ.yale.edu Language: English - Date: 1997-09-18 10:42:58 Regression analysis Time series analysis Actuarial science Variance Forecasting Standard error Autocorrelation Endogeneity Importance sampling Statistics Econometrics Data analysis
112	Bayesian MAP estimation of piecewise arcs in tempo time-series Dan Stowell1 and Elaine Chew1 Centre for Digital Music, Queen Mary, University of London Add to Reading List Source URL: c4dm.eecs.qmul.ac.uk Language: English - Date: 2012-07-12 06:23:44 Probability and statistics Statistical inference Prior probability Hidden Markov model Viterbi algorithm A priori Arc Estimation theory Bayesian statistics Statistics Markov models
113	NCEP Metrics for Evaluating Climate Models and Forecasts May 15, 2015 This document provides guidelines for evaluating the improvements in climate model performance to NCEP operational Climate Forecast System (CFS) and f Add to Reading List Source URL: www.cpc.ncep.noaa.gov Language: English - Date: 2015-05-18 04:48:52 Prediction Weather prediction Data analysis Forecasting Time series analysis Weather forecasting Madden–Julian oscillation Forecast skill Weather Atmospheric sciences Meteorology Statistical forecasting
114	Discrete Models Discrete Models Suppose that a time series of q + 1 data points y0, y1, y2, u , yq is given. A likelihood function L gives the probability that the observed data would result from the proposed stochastic Add to Reading List Source URL: www.mackichan.com Language: English - Date: 2002-03-18 12:00:12 Logarithm Mathematics Statistical theory Estimation theory Maximum likelihood
115	THRESHOLD HETEROSCEDASTICITY 1 On Conditionally Heteroscedastic AR Models with Thresholds Kung-Sik Chan, Dong Li, Shiqing Ling and Howell Tong Add to Reading List Source URL: lx2.saas.hku.hk Language: English - Date: 2012-07-03 22:05:22 Estimation theory Regression analysis Heteroscedasticity Autoregressive conditional heteroskedasticity Markov chain Variance Maximum likelihood Conditional variance Statistics Econometrics Time series analysis
116	Stat 565 Some Basic Time Series Models JanCharlotte Wickham Monday, January 20, 14 Add to Reading List Source URL: stat565.cwick.co.nz Language: English - Date: 2014-01-22 12:34:56 Noise Stochastic processes Signal processing Autocovariance Covariance function Autocorrelation White noise Stationary process Autoregressive model Statistics Time series analysis Covariance and correlation
117	http://www.springer.com 2 Nonstationary Time Series In this chapter, models for nonstationary time series are introduced. Before the characteristics of unit Add to Reading List Source URL: www.pfaffikus.de Language: English - Date: 2012-07-05 15:37:59 Dickey–Fuller test Stationary process Autoregressive integrated moving average Trend stationary Time series Random walk Order of integration Autoregressive model Stochastic Statistics Time series analysis Unit root
118	Data and bias correction for decadal climate predictions 1. Introduction Because climate models are not perfect simulated climatologies will dier somewhat from observed climatologies. The model state will drift toward Add to Reading List Source URL: wcrp-climate.org Language: English - Date: 2013-12-18 05:49:10 Data analysis Forecasting Time series analysis Weather prediction Meteorology Science Statistical forecasting Prediction Statistics
119	Further Econometric Investigation of the 2011 Reduction in Road Fatalities Add to Reading List Source URL: www.transport.govt.nz Language: English - Date: 2013-12-16 19:00:26 Statistical models Time series analysis Statistical forecasting Dummy variable Economic model Econometric model Errors and residuals in statistics Forecasting Specification Statistics Econometrics Regression analysis
120	Temporal Aggregation of Equity Return Time-Series Models Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-01-15 17:48:36 Autoregressive conditional heteroskedasticity Econometrics Time series analysis Markov models Stable distribution Stochastic volatility Economic model Log-normal distribution Normal distribution Statistics Probability and statistics Mathematical finance