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From
Forecasting Based On a SARIMA Model of Urban Malaria for Kolkata
Krishnendra S. Ganguly, Soumita Modak, Asis K. Chattopadhyay, Krishna S. Ganguly, Tapan K. Mukherjee, Ambar Dutta, Debashis Biswas
American Journal of Epidemiology and Infectious Disease
.
2016
, 4(2), 22-33 doi:10.12691/ajeid-4-2-2
Figure 1
.
Factors of Epidemiological Triad (i.e., different co-variates), e.g., Economic, Geo-Climatic, Politico-Legal, Socio-Cultural,
etc
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Figure 2
.
Kolkata in West Bengal in India
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Figure 3
.
Borough-V of Kolkata
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Figure 4
.
GIS Maps of crude SPRs for the 11wards of Borough-V for 2008-2013
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Figure 5
.
Time Series Plot
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Figure
6
.
Components of Time Series
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Figure
7
.
The correlogram of of
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Figure
8
.
The correlogram of
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Figure
9
.
The correlogram of
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Figure 10
.
The partial ac.f. plot of
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Figure 11
.
Time Series plot of Residuals
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Figure 12
.
The correlogram of residuals
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Figure 13
.
Black line: Observed Time Series, Red line: Fitted Time Series, Blue line: Forecast Time Series, Dark Grey region: 80% Confidence Interval for Forecast, Light Grey region: 95% Confidence Interval for Forecast.
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Figure 14
.
A thin blue line is added to Fig.12, showing monthly observed time series data for the year 2014
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Figure 15
.
The correlogram of departure of observed time series from our forecast time series for the year 2014
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