coevfit objectR/coev_plot_delta_theta.R
coev_plot_delta_theta.RdPlot delta theta values for all trait pairs from a fitted coevfit
object. This plot can be used to visually assess contingencies and
directionality between different variables in the coevolutionary process.
coev_plot_delta_theta(
object,
variables = NULL,
prob = 0.66,
prob_outer = 0.95,
limits = NULL
)An object of class coevfit
If NULL (default), the plot includes all coevolving variables from the model. Otherwise, a character vector of length >= 2 declaring the variables to be included in the plot.
Probability mass to include in the inner interval. Default is 0.66 (66% interval).
Probability mass to include in the outer interval. Default is 0.95 (95% interval).
If NULL (default), limits are scaled automatically to include all posterior samples. Otherwise, a numeric vector of length 2 specifying the lower and upper limits for the x-axis.
A ggplot object
This function repeatedly uses the
coev_calculate_delta_theta function under the hood to
generate a pairs plot of \(\Delta\theta\) for all variables in the model.
For more details on the definition and calculation of \(\Delta\theta\),
see help(coev_calculate_delta_theta). Note that often the posterior
distribution for \(\Delta\theta\) has long tails, meaning that the
distribution for different traits can be difficult to visualise in a single
pairs plot. If this plot does not produce satisfactory visualisations, the
user should either specify narrower limits for the x-axis or use the
coev_calculate_delta_theta function to create plots manually.
Ringen, E., Martin, J. S., & Jaeggi, A. (2021). Novel phylogenetic methods
reveal that resource-use intensification drives the evolution of "complex"
societies. EcoEvoRXiv. doi:10.32942/osf.io/wfp95
Sheehan, O., Watts, J., Gray, R. D., Bulbulia, J., Claessens, S., Ringen,
E. J., & Atkinson, Q. D. (2023). Coevolution of religious and political
authority in Austronesian societies. Nature Human Behaviour,
7(1), 38-45. 10.1038/s41562-022-01471-y
if (FALSE) { # \dontrun{
# fit dynamic coevolutionary model
fit <- coev_fit(
data = authority$data,
variables = list(
political_authority = "ordered_logistic",
religious_authority = "ordered_logistic"
),
id = "language",
tree = authority$phylogeny,
# additional arguments for cmdstanr::sample()
chains = 4,
parallel_chains = 4,
seed = 1
)
# plot delta theta values for all effects
coev_plot_delta_theta(fit)
} # }