<p>A and B. ACF and PACF plots of original schistosomisis prevalence (1956–2008); C and D. ACF and PACF plots after one order of regular differencing (1956–2008); E and F. ACF and PACF plots of original schistosomisis prevalence (1956–2012); G and H. ACF and PACF plots after one order of regular differencing (1956–2012). Dotted lines indicate 95% confidence intervals. Most of the correlations fall around zero within their 95% confidence intervals except for the one at zero lag, which indicate the series achieved stationary.</p
<p>Plots show auto-correlation of model residuals to 400 lags (400 days) for A) GLM with no random e...
<p>The error autocorrelation was one of the evaluation parameters in the modelling process. As shown...
<p>ACF=autocorrelation function, PACF=partial autocorrelation fuction. After taking a non-seasonal a...
All spikes aside from the one at 12lag failed to exceed the estimated 95% uncertainty intervals, so ...
<p>A and B show ACF and PACF of the training set. C and D show ACF and PACF of the training set afte...
Almost all spikes fell within the estimated 95% uncertainty bounds at varying lags apart from the co...
<p>The x-axis gives the number of lags in weeks and, the y-axis, the value of the correlation coeffi...
<p>Campylobacteriosis SARIMA (1, 0, 0) (2, 0, 0)<sub>12</sub> (A-C), salmonellosis SARIMA (1, 0, 0) ...
<p>Autocorrelation functions (ACF, blue) and partial rate correlation functions (PRCF, green) on the...
<p>A and C) Time series profile of the square root values of onchocerciasis cases in Oaxaca and Chia...
<p><b>A</b> Mean PACFs observed in condition H. Error bars denote the across-subjects standard devia...
<p>When we completed the ARIMA modelling (1956–2008) and drew the prediction curve (Figure 3A), we d...
(a) Autocorrelation (b) Partial autocorrelation. The ACF (autocorrelation function) values for HFRS ...
<p>A) Scatter-plot of observed versus estimated microfilarial prevalence in those aged ≥ 5 years (<i...
<p>(a) Mean value of Moran's Index computed on the 26 epidemics from the Sentinelles network, and (b...
<p>Plots show auto-correlation of model residuals to 400 lags (400 days) for A) GLM with no random e...
<p>The error autocorrelation was one of the evaluation parameters in the modelling process. As shown...
<p>ACF=autocorrelation function, PACF=partial autocorrelation fuction. After taking a non-seasonal a...
All spikes aside from the one at 12lag failed to exceed the estimated 95% uncertainty intervals, so ...
<p>A and B show ACF and PACF of the training set. C and D show ACF and PACF of the training set afte...
Almost all spikes fell within the estimated 95% uncertainty bounds at varying lags apart from the co...
<p>The x-axis gives the number of lags in weeks and, the y-axis, the value of the correlation coeffi...
<p>Campylobacteriosis SARIMA (1, 0, 0) (2, 0, 0)<sub>12</sub> (A-C), salmonellosis SARIMA (1, 0, 0) ...
<p>Autocorrelation functions (ACF, blue) and partial rate correlation functions (PRCF, green) on the...
<p>A and C) Time series profile of the square root values of onchocerciasis cases in Oaxaca and Chia...
<p><b>A</b> Mean PACFs observed in condition H. Error bars denote the across-subjects standard devia...
<p>When we completed the ARIMA modelling (1956–2008) and drew the prediction curve (Figure 3A), we d...
(a) Autocorrelation (b) Partial autocorrelation. The ACF (autocorrelation function) values for HFRS ...
<p>A) Scatter-plot of observed versus estimated microfilarial prevalence in those aged ≥ 5 years (<i...
<p>(a) Mean value of Moran's Index computed on the 26 epidemics from the Sentinelles network, and (b...
<p>Plots show auto-correlation of model residuals to 400 lags (400 days) for A) GLM with no random e...
<p>The error autocorrelation was one of the evaluation parameters in the modelling process. As shown...
<p>ACF=autocorrelation function, PACF=partial autocorrelation fuction. After taking a non-seasonal a...