brmPlot {pcvr} | R Documentation |
Models fit using growthSS inputs by fitGrowth (and similar models made through other
means) can be visualized easily using this function. This will generally be called by
growthPlot
.
brmPlot(
fit,
form,
df = NULL,
groups = NULL,
timeRange = NULL,
facetGroups = TRUE,
hierarchy_value = NULL,
vir_option = "plasma"
)
fit |
A brmsfit object, similar to those fit with |
form |
A formula similar to that in |
df |
An optional dataframe to use in plotting observed growth curves on top of the model. |
groups |
An optional set of groups to keep in the plot. Defaults to NULL in which case all groups in the model are plotted. |
timeRange |
An optional range of times to use. This can be used to view predictions for future data if the available data has not reached some point (such as asymptotic size), although prediction using splines outside of the observed range is not necessarily reliable. |
facetGroups |
logical, should groups be separated in facets? Defaults to TRUE. |
hierarchy_value |
If a hierarchical model is being plotted, what value should the hiearchical predictor be? If left NULL (the default) the mean value is used. |
vir_option |
Viridis color scale to use for plotting credible intervals. Defaults to "plasma". |
Returns a ggplot showing a brms model's credible intervals and optionally the individual growth lines.
simdf <- growthSim(
"logistic", n = 20, t = 25,
params = list("A" = c(200, 160), "B" = c(13, 11), "C" = c(3, 3.5))
)
ss <- growthSS(
model = "logistic", form = y ~ time | id / group, sigma = "spline",
list("A" = 130, "B" = 10, "C" = 3),
df = simdf, type = "brms"
)
fit <- fitGrowth(ss, backend = "cmdstanr", iter = 500, chains = 1, cores = 1)
growthPlot(fit = fit, form = y ~ time | group, groups = "a", df = ss$df)