predict.blrm | R Documentation |
blrm()
fitPredict method for blrm()
objects
## S3 method for class 'blrm'
predict(
object,
...,
kint = NULL,
ycut = NULL,
zcppo = TRUE,
fun = NULL,
funint = TRUE,
type = c("lp", "fitted", "fitted.ind", "mean", "x", "data.frame", "terms", "cterms",
"ccterms", "adjto", "adjto.data.frame", "model.frame"),
se.fit = FALSE,
codes = FALSE,
posterior.summary = c("mean", "median", "all"),
cint = 0.95
)
object, ..., type, se.fit, codes |
see |
kint |
This is only useful in a multiple intercept model such as the ordinal logistic model. There to use to second of three intercepts, for example, specify |
ycut |
for an ordinal model specifies the Y cutoff to use in evaluating departures from proportional odds, when the constrained partial proportional odds model is used. When omitted, |
zcppo |
applies only to |
fun |
a function to evaluate on the linear predictor, e.g. a function created by |
funint |
set to |
posterior.summary |
set to |
cint |
probability for highest posterior density interval. Set to |
a data frame, matrix, or vector with posterior summaries for the requested quantity, plus an attribute 'draws'
that has all the posterior draws for that quantity. For type='fitted'
and type='fitted.ind'
this attribute is a 3-dimensional array representing draws x observations generating predictions x levels of Y.
Frank Harrell
predict.lrm()
## Not run:
f <- blrm(...)
predict(f, newdata, type='...', posterior.summary='median')
## End(Not run)
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