plot.simmr_output {simmr} | R Documentation |
Plot different features of an object created from simmr_mcmc
or simmr_ffvb
.
Description
This function allows for 4 different types of plots of the simmr output
created from simmr_mcmc
or simmr_ffvb
. The
types are: histogram, kernel density plot, matrix plot (most useful) and
boxplot. There are some minor customisation options.
Usage
## S3 method for class 'simmr_output'
plot(
x,
type = c("isospace", "histogram", "density", "matrix", "boxplot"),
group = 1,
binwidth = 0.05,
alpha = 0.5,
title = if (length(group) == 1) {
"simmr output plot"
} else {
paste("simmr output plot: group", group)
},
ggargs = NULL,
...
)
Arguments
x |
An object of class |
type |
The type of plot required. Can be one or more of 'histogram', 'density', 'matrix', or 'boxplot' |
group |
Which group(s) to plot. |
binwidth |
The width of the bins for the histogram. Defaults to 0.05 |
alpha |
The degree of transparency of the plots. Not relevant for matrix plots |
title |
The title of the plot. |
ggargs |
Extra arguments to be included in the ggplot (e.g. axis limits) |
... |
Currently not used |
Details
The matrix plot should form a necessary part of any SIMM analysis since it allows the user to judge which sources are identifiable by the model. Further detail about these plots is provided in the vignette. Some code from https://stackoverflow.com/questions/14711550/is-there-a-way-to-change-the-color-palette-for-ggallyggpairs-using-ggplot accessed March 2023
Value
one or more of 'histogram', 'density', 'matrix', or 'boxplot'
Author(s)
Andrew Parnell <andrew.parnell@mu.ie>, Emma Govan
See Also
See simmr_mcmc
and simmr_ffvb
for
creating objects suitable for this function, and many more examples. See
also simmr_load
for creating simmr objects,
plot.simmr_input
for creating isospace plots,
summary.simmr_output
for summarising output.
Examples
# A simple example with 10 observations, 2 tracers and 4 sources
# The data
data(geese_data)
# Load into simmr
simmr_1 <- with(
geese_data_day1,
simmr_load(
mixtures = mixtures,
source_names = source_names,
source_means = source_means,
source_sds = source_sds,
correction_means = correction_means,
correction_sds = correction_sds,
concentration_means = concentration_means
)
)
# Plot
plot(simmr_1)
# MCMC run
simmr_1_out <- simmr_mcmc(simmr_1)
# Plot
plot(simmr_1_out) # Creates all 4 plots
plot(simmr_1_out, type = "boxplot")
plot(simmr_1_out, type = "histogram")
plot(simmr_1_out, type = "density")
plot(simmr_1_out, type = "matrix")