plot.insilico | R Documentation |
Produce a bar plot of the CSMFs for a fitted "insilico"
object.
## S3 method for class 'insilico' plot( x, type = c("errorbar", "bar", "compare")[1], top = 10, causelist = NULL, which.sub = NULL, xlab = "Causes", ylab = "CSMF", title = "Top CSMF Distribution", horiz = TRUE, angle = 60, fill = "lightblue", err_width = 0.4, err_size = 0.6, point_size = 2, border = "black", bw = TRUE, ... )
x |
fitted |
type |
An indicator of the type of chart to plot. "errorbar" for line plots of only the error bars on single population; "bar" for bar chart with error bars on single population; "compare" for line charts on multiple sub-populations. |
top |
The number of top causes to plot. If multiple sub-populations are to be plotted, it will plot the union of the top causes in all sub-populations. |
causelist |
The list of causes to plot. It could be a numeric vector
indicating the position of the causes in the InterVA cause list (see
|
which.sub |
Specification of which sub-population to plot if there are
multiple and |
xlab |
Labels for the causes. |
ylab |
Labels for the CSMF values. |
title |
Title of the plot. |
horiz |
Logical indicator indicating if the bars are plotted horizontally. |
angle |
Angle of rotation for the texts on x axis when |
fill |
The color to fill the bars when |
err_width |
Size of the error bars. |
err_size |
Thickness of the error bar lines. |
point_size |
Size of the points. |
border |
The color to color the borders of bars when |
bw |
Logical indicator for setting the theme of the plots to be black and white. |
... |
Not used. |
To-do
Zehang Li, Tyler McCormick, Sam Clark
Maintainer: Zehang Li <lizehang@uw.edu>
Tyler H. McCormick, Zehang R. Li, Clara Calvert, Amelia C. Crampin, Kathleen Kahn and Samuel J. Clark Probabilistic cause-of-death assignment using verbal autopsies, Journal of the American Statistical Association (2016), 111(515):1036-1049.
insilico
, summary.insilico
## Not run: data(RandomVA1) ## ## Scenario 1: without sub-population specification ## fit1<- insilico(RandomVA1, subpop = NULL, Nsim = 1000, burnin = 500, thin = 10 , seed = 1, auto.length = FALSE) # basic line plot plot(fit1) # basic bar plot plot(fit1, type = "bar") # line plot with customized look plot(fit1, top = 15, horiz = FALSE, fill = "gold", bw = TRUE, title = "Top 15 CSMFs", angle = 70, err_width = .2, err_size = .6, point_size = 2) ## ## Scenario 2: with sub-population specification ## data(RandomVA2) fit2<- insilico(RandomVA2, subpop = list("sex"), Nsim = 1000, burnin = 500, thin = 10 , seed = 1, auto.length = FALSE) summary(fit2) # basic side-by-side line plot for all sub-populations plot(fit2, type = "compare", main = "Top 5 causes comparison") # basic line plot for specific sub-population plot(fit2, which.sub = "Women", main = "Top 5 causes for women") # customized plot with only specified causes # the cause names need not be exact as InterVA cause list # substrings in InterVA cause list is enough for specification # e.g. the following two specifications are the same some_causes_1 <- c("HIV/AIDS related death", "Pulmonary tuberculosis") some_causes_2 <- c("HIV", "Pulmonary") plot(fit2, type = "compare", horiz = FALSE, causelist = some_causes_1, title = "HIV and TB fractions in two sub-populations", angle = 20) ## End(Not run)
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