c.reliabilitydiag: Combining reliability diagram objects

In aijordan/reliabilitydiag: Reliability Diagrams Using Isotonic Regression

Combining reliability diagram objects

Description

Combine two or more 'reliabilitydiag' objects that are based on the same observations. Other objects are coerced by as.reliabilitydiag before combination.

Usage

## S3 method for class 'reliabilitydiag'
c(
  ...,
  tol = sqrt(.Machine$double.eps),
  xtype = NULL,
  xvalues = NULL,
  region.level = 0.9,
  region.method = NULL,
  region.position = "diagonal",
  n.boot = 100
)

Arguments

...	objects to be concatenated.
tol	accuracy when comparing y in 'reliabilitydiag' objects.
xtype	a string specifying whether the prediction values should be treated as "continuous" or "discrete".
xvalues	a numeric vector of possible prediction values; values in x are rounded to the nearest value in xvalues and xtype is set to "discrete".
region.level	a value in (0, 1) specifying the level at which consistency or confidence regions are calculated.
region.method	a string specifying whether "resampling", "continuous_asymptotics", or "discrete_asymptotics" are used to calculate consistency/confidence regions.
region.position	a string specifying whether consistency regions around the "diagonal" or confidence regions around the "estimate" are calculated.
n.boot	the number of bootstrap samples when region.method == "resampling".

Value

an object inheriting from the class 'reliabilitydiag'.

See Also

as.reliabilitydiag, [.reliabilitydiag.

Examples

data("precip_Niamey_2016", package = "reliabilitydiag")

X <- precip_Niamey_2016[c("EMOS", "ENS")]
Y <- precip_Niamey_2016$obs
r0 <- reliabilitydiag0(Y)
r1 <- c(r0, X, EPC = precip_Niamey_2016$EPC, region.level = NA)
r1
c(r1, reliabilitydiag(Logistic = precip_Niamey_2016$Logistic, y = Y))

aijordan/reliabilitydiag documentation built on June 29, 2022, 4:18 p.m.