predict.mevr: TMEV prediction

In mevr: Fitting the Metastatistical Extreme Value Distribution MEVD

TMEV prediction

Description

Takes a mevr object where the TMEV has been fitted to rainfall data and calculates bamlss predictions for the distributional parameters and the model terms. Basically a wrapper to the corresponding function predict.bamlss

Usage

## S3 method for class 'mevr'
predict(object, newdata, term, ...)

Arguments

object	Object of class mevr, fitted with the TMEV.
newdata	A data frame with the model covariates (year, yday) at which predictions are required. Note that depending on argument term, only covariates that are needed by the corresponding model terms need to be supplied. If not supplied, predictions are made on the data supplied by the fitted object x.
term	Character of the model terms for which predictions shall be calculated. Can only be "year" or "yday". If not specified, predictions for all terms are calculated.
...	Arguments passed to prediction functions that are part of a bamlss.family object, i.e., the objects has a $predict() function that should be used instead.

Details

See also the details of ftmev for an explanation of the model terms used to fit the temporal trend of the Weibull parameters. The basis dimensions yday_ti_shape_k, yday_ti_scale_k, year_ti_shape_k, year_ti_scale_k are taken from the fitting process, i.e. the call to ftmev.

Value

A data.frame with the supplied covariables and the predicted parameters.

See Also

ftmev, predict.bamlss

Examples

data(dailyrainfall)

# restrict for the sake of speed
idx <- which(as.POSIXlt(dailyrainfall$date)$year + 1900 < 1976)
data <- dailyrainfall[idx, ]

f <- ftmev(data, minyears = 5)
predict(f, term = "year")

mevr documentation built on June 30, 2024, 9:06 a.m.