
Plot summary statistics related to variable selection
# S3 method for vsel
plot(
x,
nterms_max = NULL,
stats = "elpd",
deltas = FALSE,
alpha = 0.32,
baseline = NULL,
...
)
Maximum submodel size for which the statistics are
calculated. For plot.vsel
it must be at least 1.
One or several strings determining which statistics to calculate. Available statistics are:
elpd: (Expected) sum of log predictive densities
mlpd: Mean log predictive density, that is, elpd divided by the number of datapoints.
mse: Mean squared error (gaussian family only)
rmse: Root mean squared error (gaussian family only)
acc/pctcorr: Classification accuracy (binomial family only)
auc: Area under the ROC curve (binomial family only)
Default is "elpd"
.
If TRUE
, the submodel statistics are estimated relative
to the baseline model (see argument baseline
) instead of estimating
the actual values of the statistics. Defaults to FALSE
.
A number indicating the desired coverage of the credible
intervals. For example alpha=0.32
corresponds to 68% probability
mass within the intervals, that is, one standard error intervals.
Either 'ref' or 'best' indicating whether the baseline is the reference model or the best submodel found. Default is 'ref' when the reference model exists, and 'best' otherwise.
Currently ignored.
# NOT RUN {
### Usage with stanreg objects
if (requireNamespace('rstanarm', quietly=TRUE)) {
n <- 30
d <- 5
x <- matrix(rnorm(n*d), nrow=n)
y <- x[,1] + 0.5*rnorm(n)
data <- data.frame(x,y)
fit <- rstanarm::stan_glm(y ~ X1 + X2 + X3 + X4 + X5, gaussian(),
data=data, chains=2, iter=500)
vs <- cv_varsel(fit)
plot(vs)
}
# }
# NOT RUN {
# }
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