isodistrreg (version 0.6.0)

qpred: Quantile function of IDR or raw forecasts

Description

Evaluate the the quantile function of IDR predictions or of unprocessed forecasts in a data.frame.

Usage

qpred(predictions, quantiles)
# S3 method for idr
qpred(predictions, quantiles)
# S3 method for data.frame
qpred(predictions, quantiles)

Value

A matrix of forecasts for the desired quantiles, one column per quantile.

Arguments

predictions

either an object of class idr (output of predict.idrfit), or a data.frame of numeric variables. In the latter case, quantiles are computed using the empirical distribution of the variables in predictions.

quantiles

numeric vector of desired quantiles.

Details

The quantiles are defined as lower quantiles, that is, $$ q(u) = inf(x: cdf(x) >= u), $$ except for $$u = 0$$ when the lower endpoint of the support is returned.

See Also

predict.idrfit, cdf, qscore

Examples

data("rain")

## Postprocess HRES forecast using data of 3 years

X <- rain[1:(3 * 365), "HRES", drop = FALSE]
y <- rain[1:(3 * 365), "obs"]

fit <- idr(y = y, X = X)

## Compute 95%-quantile forecast given that the HRES forecast is
## 2.5 mm, 5 mm or 10 mm

predictions <- predict(fit, data = data.frame(HRES = c(2.5, 5, 10)))
qpred(predictions, quantiles = 0.95)