Create a forecast
object for quantile-based forecasts. See more information
on forecast types and expected input formats by calling ?
as_forecast()
.
When creating a forecast_quantile
object from a forecast_sample
object,
the quantiles are estimated by computing empircal quantiles from the samples
via quantile()
. Note that empirical quantiles are a biased estimator for
the true quantiles in particular in the tails of the distribution and
when the number of available samples is low.
Usage
as_forecast_quantile(data, ...)
# Default S3 method
as_forecast_quantile(
data,
forecast_unit = NULL,
observed = NULL,
predicted = NULL,
quantile_level = NULL,
...
)
# S3 method for class 'forecast_sample'
as_forecast_quantile(
data,
probs = c(0.05, 0.25, 0.5, 0.75, 0.95),
type = 7,
...
)
Arguments
- data
A data.frame (or similar) with predicted and observed values. See the details section of
as_forecast()
for additional information on required input formats.- ...
Unused
- forecast_unit
(optional) Name of the columns in
data
(after any renaming of columns) that denote the unit of a single forecast. Seeget_forecast_unit()
for details. IfNULL
(the default), all columns that are not required columns are assumed to form the unit of a single forecast. If specified, all columns that are not part of the forecast unit (or required columns) will be removed.- observed
(optional) Name of the column in
data
that contains the observed values. This column will be renamed to "observed".- predicted
(optional) Name of the column in
data
that contains the predicted values. This column will be renamed to "predicted".- quantile_level
(optional) Name of the column in
data
that contains the quantile level of the predicted values. This column will be renamed to "quantile_level". Only applicable to quantile-based forecasts.- probs
A numeric vector of quantile levels for which quantiles will be computed. Corresponds to the
probs
argument inquantile()
.- type
Type argument passed down to the quantile function. For more information, see
quantile()
.
See also
Other functions to create forecast objects:
as_forecast
,
as_forecast_binary()
,
as_forecast_nominal()
,
as_forecast_point()
,
as_forecast_sample()