12 research outputs found

    The ACF graph and PACF graph of the ARIMA (0,1,0) × (0,1,0)<sub>12</sub> model.

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    <p>ACF=autocorrelation function, PACF=partial autocorrelation fuction. After taking a non-seasonal and seasonal difference, the TB report rate series shows dominant peaks in the autocorrelation functions lags 12, 24 and 36 months indicating a strong seasonal pattern in the report rate of TB in Hubei Province, China.</p

    Proportion of tuberculosis cases by month of report.

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    <p>Month begins with January and is abbreviated by first letter. It shows that TB cases exhibit a peak in March and a trough in December across the entire study period.</p

    The ACF graph and PACF graph of the residuals for the ARIMA (2,1,0) × (0,1,1)<sub>12</sub> model.

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    <p>ACF=autocorrelation function, PACF=partial autocorrelation fuction. As their correlation values are not outside the confidence intervals (CI) limits, the residuals error is considered to be white noise indicating that this model is appropriate for prediction. </p

    The selection of the spread of the GRNN-ARIMA model.

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    <p>ARIMA=the autoregressive integrated moving average; GRNN=the generalized regression neural network. The spread values between 0.5 and 1.5 with an interval of 0.05 were selected to find the minimum RMSE for the testing samples. When the spread was 0.95, the RMSE was lowest.</p
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