Description Usage Arguments Details Value
Computes IDR predictions with bootstrap aggregating (bagging) or subsample aggregation (subagging).
1 2 3 4 |
y |
numeric vector (the response variable). |
X |
data frame of numeric or ordered factor variables (the regression covariates). |
groups |
named vector of length |
orders |
named vector giving for each group in |
stoch |
stochastic order constraint used for estimation. Default is
|
pars |
parameters for quadratic programming optimization (only relevant
if |
progress |
display progressbar ( |
newdata |
|
digits |
number of decimal places for the predictive CDF. |
interpolation |
interpolation method for univariate data. Default is
|
b |
number of (su)bagging samples. |
p |
size of (su)bagging samples relative to training data. |
replace |
draw samples with ( |
grid |
grid on which the predictive CDFs are evaluated. Default are
the unique values of |
This function draws b
times a random subsample of size
ceiling(nrow(X)*p)
) from the training data, fits IDR to each
subsample, computes predictions for the new data supplied in newdata
,
and averages the predictions derived from the b
subsamples. There are
no default values for b
and p
.
A list of predictions, see predict.idrfit
.
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