Plots within-chain parameter correlations (upper triangle) and corresponding scatterplots (lower triangle) to visualize parameter sloppiness.
pairs_posterior(
emc,
selection = "alpha",
scale_subjects = TRUE,
do_plot = TRUE,
N = 500,
...
)
Invisibly returns a matrix with the correlations between the parameters.
An emc object
A Character string. Indicates which parameter type to
plot (alpha
, mu
, variance
, covariance
, correlation
).
Boolean. To standardize each participant with selection = "alpha"
,
by subtracting the mean and divding by the standard deviation. This ensures the plot has every participant on the same scale.
Boolean. Whether to plot the pairs plot, if FALSE
, only the correlations
are returned.
Integer for maximum number of iterations used (defaults to 500). If number of samples in stage or selection exceeds N, a random subset will be taken of size N
Optional arguments that can be passed to get_pars
If selection = alpha
the parameter chains are concatenated across participants,
(after standardizing if scale_subjects = TRUE
) and then correlated.
# \donttest{
# Plot the sloppiness for the individual-level subjects
pairs_posterior(samples_LNR, selection = "alpha")
# We can also choose group-level parameters and subsets of the parameter space
pairs_posterior(samples_LNR, use_par = c("m", "t0"), selection = "sigma2")
# }
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