plotMethods for function plot for different S4 classes: sbm, sbm_ci, and loggrowth.
signature(x = "sbm")plot.sbm(x, y, ...):
Plots the results of the Swash-Backwash Model. This generates two plots:
Edges over time.
Total infections per time unit.
Arguments:
x: An object of class sbm representing the results of the Swash-Backwash Model.
y: Optional argument for additional customization, such as plot style or axis labels.
...: Additional graphical parameters that can be passed to control plot appearance.
Details: This method is used to visualize the output of the Swash-Backwash Model, providing insight into the dynamics of the modeled epidemic.
signature(x = "sbm_ci")plot.sbm_ci(x, y, ...):
Plots the results of bootstrap confidence intervals for the Swash-Backwash Model. This generates a single figure with six subplots:
\(S_A\) (susceptible population),
\(I_A\) (infected population),
\(R_A\) (recovered population),
\(t_{FE}\) (final epidemic time),
\(t_{LE}\) (last epidemic time),
\(R_{0A}\) (basic reproduction number).
Arguments:
x: An object of class sbm_ci containing the bootstrap confidence intervals for the Swash-Backwash Model.
y: Optional argument for additional customization, such as plot style or axis labels.
...: Additional graphical parameters for fine-tuning the plots.
Details: This method is used to visualize the bootstrap confidence intervals for various parameters of the Swash-Backwash Model.
signature(x = "countries")plot.sbm(x, y = NULL, col_bars = "grey", col_ci = "red"):
Plots the results of the between-countries analysis via Swash-Backwash Model. This generates four plots:
Indicator for country 1
Indicator for country 2
Boxplots of the distribution of the indicator in country 1 and 2
Distribution of the difference between the indicators of country 1 and 2
Arguments:
x: An object of class countries representing the results of the Swash-Backwash Model country analysis.
y: Not relevant
col_bars: Color of bars
col_ci: Color of confidence intervals
Details: This method is used to visualize the output of the Swash-Backwash Model, providing insight into the dynamics of the modeled epidemic.
signature(x = "loggrowth")plot.loggrowth(x, y, ...):
Plots the results of the logistic growth model, including:
Observed values,
Predicted values,
First derivative (growth rate).
Arguments:
x: An object of class loggrowth containing the data for the logistic growth model.
y: Optional argument for additional customization of the plot (e.g., color, labels).
...: Additional arguments for graphical parameters.
Details: This method is useful for visualizing the observed and predicted growth patterns in an epidemic or similar phenomena modeled by logistic growth.
Thomas Wieland