![]() ![]() A random variable of this form can be viewed (as usual) as a combination (correlations with its own prior deviations from the mean) remain constant over The latter condition means that its autocorrelations ![]() Its variations around its mean have a constant amplitude, and it wiggles in aĬonsistent fashion, i.e., its short-term random time patterns always look Random variable that is a time series is stationary if its statistical With nonlinear transformations such as logging or deflating (if necessary). “stationary” by differencing (if necessary), perhaps in conjunction Models for forecasting a time series which can be made to be ![]() Forecasting equation: ARIMA models are, in theory, the most general class of ![]()
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