The peak week during each influenza season was defined when the greatest unweighted moving average was observed in individual prefectures.
The fourth definition, also NSW specific (NSW2), proposes that a heat wave is any three day period with greater than the 90th percentile of maximum temperatures for that month in addition to a moving average of greater than 27°C maximum temperature for the 3 day period.
The lower we find a position above the 200-day moving average, the greater the potential edge, as demand returns and prices move higher once again.
The method merges the flexibility of principal component analysis (PCA) models and the greater sensitivity of the exponentially-weighted moving average (EWMA) and cumulative sum (CUSUM) control charts to insidious changes.
Decay rate differences lead to a frequently observed feature of seasonal adjustment filters of all seasonal ARIMA models with a seasonal moving average factor: The greater the value of (Theta ) is, the less localized and adaptive but more stable the estimate will be.
Mean weekly autochthonous DF incidence increased 10-fold (to mean autochthonous DF incidence of 0.4 relative to an overall mean autochthonous DF incidence of 0.04) when the 3-week lagged moving average rainfall was greater or equal to 27 mm.
A classic version of this model starts by taking a 12-day exponential moving average of the stock price (greater importance given to more recent prices) and subtracting the 26-day exponential moving average.
The mean 3-week lagged moving average rainfall in Cairns was greater than that of Townsville (t=5.13, P<0.000).
In cities with no influenza data available, we included a dummy variable that was assigned the value of 1 when the 7-day moving average of respiratory mortality was greater than the 90th percentile of the city-specific distribution.
The mean 4-week lagged moving average minimum temperature in Cairns was greater than that of Townsville (t=4.29, P<0.000).
Three- to 12-day moving average coefficients of NO2 were 50 400% greater than individual-day lag coefficients and steadily increased in magnitude as the size of the moving average increased; however, the ORs for moving averages were much smaller, given the smaller absolute increment represented by a 1-day increase in the longer moving averages.
