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Model visualization

library(serosv)

Visualize model

To visualize the model, user can simply use function plot

hav <- hav_be_1993_1994
model <- fp_model(
  hav,
  p=c(1.5, 1.6), link="cloglog")
plot(model)

If implementation for confidence interval calculation is not yet available, plot function would simply visualize seroprevalence line

rubella <- rubella_uk_1986_1987

farrington_md <- farrington_model(
   rubella,
   start=list(alpha=0.07,beta=0.1,gamma=0.03)
   )
plot(farrington_md)

Customize the plot

Built-in function

serosv offers the function set_plot_style() to customize some key attributes of the plot.

Current modifiable attributes include color, linetype for seroprevalence, foi and fill color for confidence interval

hav_mod <- polynomial_model(hav_bg_1964, k=3)

# customize plot
plot(hav_mod) +
  set_plot_style(
    sero = "#3de071",
    foi = "#2f22e0",
    ci = "#aaf2b2",
    foi_line = "dotted", 
    sero_line = "dotdash"
  )
#> Scale for colour is already present.
#> Adding another scale for colour, which will replace the existing scale.
#> Scale for linetype is already present.
#> Adding another scale for linetype, which will replace the existing scale.
#> Scale for fill is already present.
#> Adding another scale for fill, which will replace the existing scale.

ggplot2 functions

Since serosv uses ggplot2 for plotting, the returned plot is a gg object meaning any standard ggplot2 layer can be appended with + for further configurations.

# return gg object
class(plot(hav_mod))
#> [1] "gg"     "ggplot"

Examples

library(ggplot2)

# Set x and y limits
plot(hav_mod) +
  coord_cartesian(xlim = c(0, 50), ylim = c(0, 1.5))
#> Coordinate system already present. Adding new coordinate system, which will
#> replace the existing one.


# Configure the plot theme
plot(hav_mod) +
  theme_bw()


# Set titles and omit legends
plot(hav_mod) +
  theme_bw() +
  ggtitle("Age-stratified Hepatitis A prevalence in Bulgaria (1964)") +
  guides(
    colour = "none",
    linetype = "none",
    fill = "none"
  )

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.