Description Usage Arguments Value Author(s) See Also Examples
Retrieve or set the names of resampling-based prediction error results, retrieve or set the identifiers of the models, or retrieve the number of prediction error results or included models.
1 2 3 4 5 6 7 8 9 10 11 |
x |
an object inheriting from class |
value |
a vector of replacement values. |
peNames
returns the names of the prediction error results. The
replacement function thereby returns them invisibly.
fits
returns the identifiers of the models for objects inheriting
from class "perrySelect"
and NULL
for objects inheriting from
class "perry"
. The replacement function thereby returns those values
invisibly.
npe
returns the number of prediction error results.
nfits
returns the number of models included in objects inheriting
from class "perrySelect"
and NULL
for objects inheriting from
class "perry"
.
Andreas Alfons
perryFit
, perrySelect
,
perryTuning
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | library("perryExamples")
data("coleman")
set.seed(1234) # set seed for reproducibility
## set up folds for cross-validation
folds <- cvFolds(nrow(coleman), K = 5, R = 10)
## compare raw and reweighted LTS estimators for
## 50% and 75% subsets
# 50% subsets
fit50 <- ltsReg(Y ~ ., data = coleman, alpha = 0.5)
cv50 <- perry(fit50, splits = folds, fit = "both",
cost = rtmspe, trim = 0.1)
# 75% subsets
fit75 <- ltsReg(Y ~ ., data = coleman, alpha = 0.75)
cv75 <- perry(fit75, splits = folds, fit = "both",
cost = rtmspe, trim = 0.1)
# combine results into one object
cv <- perrySelect("0.5" = cv50, "0.75" = cv75)
cv
# "perry" object
npe(cv50)
nfits(cv50)
peNames(cv50)
peNames(cv50) <- c("improved", "initial")
fits(cv50)
cv50
# "perrySelect" object
npe(cv)
nfits(cv)
peNames(cv)
peNames(cv) <- c("improved", "initial")
fits(cv)
fits(cv) <- 1:2
cv
|
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