reliability: Reliability Diagram for MultiQR

In jbrowell/ProbCast: Flexible Probabilistic Forecasting

Reliability Diagram for MultiQR

Description

Calculated empirical exceedence of each quantile and plots a reliabiltiy diagram for a MultiQR object.

Optionally, results may be split by cross-validation fold or covariate and/or confidence intervals may be estimated.

Usage

reliability(
  qrdata,
  realisations,
  kfolds = NULL,
  subsets = NULL,
  breaks = 4,
  bootstrap = NULL,
  plot.it = T,
  ...
)

Arguments

qrdata	MultiQR object.
realisations	Vector of realisations corresponding to rows of qrdata. Missing data as NAs accepted.
kfolds	Optional vector of cross-validation fold labels corresponding to rows of qrdata. Cannot be used with subsets.
subsets	Optional vector of covariates to bin data by. Breaks between bins are the empirical quantiles of subsets by default or all unique factors or charater strings. Custom breaks may be specifed, see breaks. Cannot be used with kfolds.
breaks	Either the number of quantiles to use to bin subsets by (resulting in breaks+1 bins, defaults to breaks=4), or, if length(breaks) > 1, a vector of spcific break points. Only used if subsets provided. points. subsets must be provided.
bootstrap	Number of boostrap samples used to generate 95% confidence intervals.
plot.it	boolean. Make a plot?
...	Additional arguments passed to plot().

Details

Missing values in realisations are handled by na.rm=T when calculating average exceedence of a given quantile.

Value

Reliability data and, if plot.it=TRUE, a reliability diagram.

Author(s)

Jethro Browell, [e-mail]

jbrowell/ProbCast documentation built on July 20, 2024, 1:53 p.m.