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Examples
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The NARMAX algorithm (nonlinear auto-regressive moving average exogenous) multiple input multiple output (MIMO) mentioned in Rossow/Aires paper is covered in detail in Ref #6.
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Two null-hypothesis have been used to calculate the probability that such series of warm record years may arise by chance in stationary, but serially correlated, series: an auto-regressive process of order 1 and long-memory process.
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Two null-hypothesis have been used to calculate the probability that such series of warm record years may arise by chance in stationary, but serially correlated, series: an auto-regressive process of order 1 and long-memory process.
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Two null-hypothesis have been used to calculate the probability that such series of warm record years may arise by chance in stationary, but serially correlated, series: an auto-regressive process of order 1 and long-memory process.
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So what is suggested here is to run one model with sunspot time series data and see if the sunspots are significant when AR terms are used to measure the auto-regressive components and check for stationarity.
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In an article published in the American Economic Review in 1972, then-assistant professor Charles Nelson showed that with the use of Box-Jenkins time series analysis, a simple time-series model incorporating auto-regressive elements, of course performed better than the FMP model in predicting economic growth one quarter out.
Pelletier [2002] on Temperature Autocorrelation « Climate Audit 2005
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So in addition to being non-linear in its response to temp, the ring growth depends on temp in the previous year, which means you need to model it as auto-regressive, otherwise the coefficients will be biased.
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I also used an AR (1) covariance matrix (auto-regressive, first order).
Baseball Prospectus 2010
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• Ability to model default using variables which change randomly in an auto-regressive moving average fashion
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• Ability to model default using variables which change randomly in an auto-regressive moving average fashion
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