perry (version 0.3.1)

summary.perry: Summarize resampling-based prediction error results

Description

Produce a summary of resampling-based prediction error results.

Usage

# S3 method for perry
summary(object, ...)
# S3 method for perrySelect
summary(object, ...)
# S3 method for perryTuning
summary(object, ...)

Arguments

object

an object inheriting from class "perry" or "perrySelect" that contains prediction error results (note that the latter includes objects of class "perryTuning").

…

currently ignored.

Value

An object of class "summary.perry", "summary.perrySelect" or "summary.perryTuning", depending on the class of object.

See Also

perryFit, perrySelect, perryTuning, summary

Examples

# NOT RUN {
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

# summary of the results with the 50% subsets
summary(cv50)
# summary of the combined results
summary(cv)
# }