Return a plot or dataframe showing the point estimates from each model, along with confidence intervals based on the estimated standard errors.
plotCoefs(
fit,
true = FALSE,
alpha = 0.05,
plot = TRUE,
col = "blue",
flip = TRUE,
data = NULL,
select = TRUE,
size = 1,
labels = TRUE,
title = NULL,
vars = "all"
)
Output from fitNetwork
, bootNet
, or
resample
. Can also be the fixedNets
or
betweenNet
elements of the mlGVAR
output.
An adjacency matrix containing the true parameter values, if known. This can be used in conjunction with a simulated network, in that the user can supply the true network and plot those values against the estimated values.
Alpha level that is used to compute confidence intervals.
Logical. If FALSE
, a dataframe containing all of the
confidence interval data will be returned.
Character string. Color of the points associated with the
true
values.
Logical. If FALSE
, the facets will be turned 90 degrees.
Supply the original dataset if not already included in the
fit
object.
Relevant to the resample
output. Determines
whether all variables should be plotted, or only those that were selected
according to the resampling or variable selection procedure.
Numeric. Size of the point estimates.
If logical, determines whether or not variable labels should be included. If a character vector, can be used to customize variable labels.
Custom plot title.
Defaults to "all"
. Determines which variables should be
plotted.
Plot displaying estimated model coefficients and confidence intervals.
This is differentiated from the output of bootNet
and
plotBoot
in that the confidence intervals are computed directly
from model parameters rather than estimated from bootstrapping.
# NOT RUN {
x <- fitNetwork(ggmDat)
plot(x, which.net = 'coefs')
plotCoefs(x) # This is the same as the above command
# }
Run the code above in your browser using DataLab